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openbb_platform/providers/benzinga/README.md

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+# OpenBB Benzinga Provider
+
+This extension integrates the [Benzinga](https://www.benzinga.com/) data provider into the OpenBB Platform.
+
+## Installation
+
+To install the extension:
+
+```bash
+pip install openbb-benzinga
+```
+
+Documentation available [here](https://docs.openbb.co/platform/developer_guide/contributing).

openbb_platform/providers/benzinga/__init__.py

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+"""Benzinga Provider."""

openbb_platform/providers/benzinga/openbb_benzinga/__init__.py

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+"""Benzinga provider module."""
+
+from openbb_benzinga.models.analyst_search import BenzingaAnalystSearchFetcher
+from openbb_benzinga.models.company_news import BenzingaCompanyNewsFetcher
+from openbb_benzinga.models.price_target import BenzingaPriceTargetFetcher
+from openbb_benzinga.models.world_news import BenzingaWorldNewsFetcher
+from openbb_core.provider.abstract.provider import Provider
+
+benzinga_provider = Provider(
+    name="benzinga",
+    website="https://www.benzinga.com",
+    description="""Benzinga is a financial data provider that offers an API
+focused on information that moves the market.""",
+    credentials=["api_key"],
+    fetcher_dict={
+        "AnalystSearch": BenzingaAnalystSearchFetcher,
+        "CompanyNews": BenzingaCompanyNewsFetcher,
+        "WorldNews": BenzingaWorldNewsFetcher,
+        "PriceTarget": BenzingaPriceTargetFetcher,
+    },
+    repr_name="Benzinga",
+)

openbb_platform/providers/benzinga/openbb_benzinga/models/__init__.py

@@ -0,0 +1 @@
+"""Benzinga Provider Models."""

openbb_platform/providers/benzinga/openbb_benzinga/models/analyst_search.py

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+"""Benzinga Analyst Search Model."""
+
+# pylint: disable=unused-argument
+
+from datetime import (
+    date as dateType,
+    timezone,
+)
+from typing import Any, Dict, List, Optional
+
+from openbb_core.app.model.abstract.error import OpenBBError
+from openbb_core.provider.abstract.fetcher import Fetcher
+from openbb_core.provider.standard_models.analyst_search import (
+    AnalystSearchData,
+    AnalystSearchQueryParams,
+)
+from openbb_core.provider.utils.errors import EmptyDataError
+from pydantic import Field, field_validator, model_validator
+
+
+class BenzingaAnalystSearchQueryParams(AnalystSearchQueryParams):
+    """Benzinga Analyst Search Query.
+
+    Source: https://docs.benzinga.io/benzinga-apis/calendar/get-analysts
+    """
+
+    __alias_dict__ = {
+        "analyst_ids": "analyst",
+        "firm_ids": "firm",
+        "limit": "pageSize",
+    }
+    __json_schema_extra__ = {
+        "analyst_name": {"multiple_items_allowed": True},
+        "firm_name": {"multiple_items_allowed": True},
+        "analyst_ids": {"multiple_items_allowed": True},
+        "firm_ids": {"multiple_items_allowed": True},
+        "fields": {"multiple_items_allowed": True},
+    }
+
+    analyst_ids: Optional[str] = Field(
+        default=None,
+        description="List of analyst IDs to return.",
+    )
+    firm_ids: Optional[str] = Field(
+        default=None,
+        description="Firm IDs to return.",
+    )
+    limit: Optional[int] = Field(
+        default=100,
+        description="Number of results returned. Limit 1000.",
+    )
+    page: Optional[int] = Field(
+        default=0,
+        description="Page offset. For optimization,"
+        + " performance and technical reasons, page offsets"
+        + " are limited from 0 - 100000."
+        + " Limit the query results by other parameters such as date.",
+    )
+    fields: Optional[str] = Field(
+        default=None,
+        description="Fields to include in the response."
+        " See https://docs.benzinga.io/benzinga-apis/calendar/get-ratings to learn about the available fields.",
+    )
+
+
+class BenzingaAnalystSearchData(AnalystSearchData):
+    """Benzinga Analyst Search Data."""
+
+    __alias_dict__ = {
+        "analyst_id": "id",
+        "last_updated": "updated",
+        "overall_std_dev": "overall_stdev",
+        "gain_count_1m": "1m_gain_count",
+        "loss_count_1m": "1m_loss_count",
+        "average_return_1m": "1m_average_return",
+        "std_dev_1m": "1m_stdev",
+        "smart_score_1m": "1m_smart_score",
+        "success_rate_1m": "1m_success_rate",
+        "gain_count_3m": "3m_gain_count",
+        "loss_count_3m": "3m_loss_count",
+        "average_return_3m": "3m_average_return",
+        "std_dev_3m": "3m_stdev",
+        "smart_score_3m": "3m_smart_score",
+        "success_rate_3m": "3m_success_rate",
+        "gain_count_6m": "6m_gain_count",
+        "loss_count_6m": "6m_loss_count",
+        "average_return_6m": "6m_average_return",
+        "std_dev_6m": "6m_stdev",
+        "gain_count_9m": "9m_gain_count",
+        "loss_count_9m": "9m_loss_count",
+        "average_return_9m": "9m_average_return",
+        "std_dev_9m": "9m_stdev",
+        "smart_score_9m": "9m_smart_score",
+        "success_rate_9m": "9m_success_rate",
+        "gain_count_1y": "1y_gain_count",
+        "loss_count_1y": "1y_loss_count",
+        "average_return_1y": "1y_average_return",
+        "std_dev_1y": "1y_stdev",
+        "smart_score_1y": "1y_smart_score",
+        "success_rate_1y": "1y_success_rate",
+        "gain_count_2y": "2y_gain_count",
+        "loss_count_2y": "2y_loss_count",
+        "average_return_2y": "2y_average_return",
+        "std_dev_2y": "2y_stdev",
+        "smart_score_2y": "2y_smart_score",
+        "success_rate_2y": "2y_success_rate",
+        "gain_count_3y": "3y_gain_count",
+        "loss_count_3y": "3y_loss_count",
+        "average_return_3y": "3y_average_return",
+        "std_dev_3y": "3y_stdev",
+        "smart_score_3y": "3y_smart_score",
+        "success_rate_3y": "3y_success_rate",
+    }
+
+    analyst_id: Optional[str] = Field(
+        default=None,
+        description="ID of the analyst.",
+    )
+    firm_id: Optional[str] = Field(
+        default=None,
+        description="ID of the analyst firm.",
+    )
+    smart_score: Optional[float] = Field(
+        default=None,
+        description="A weighted average of the total_ratings_percentile,"
+        + " overall_avg_return_percentile, and overall_success_rate",
+    )
+    overall_success_rate: Optional[float] = Field(
+        default=None,
+        description="The percentage (normalized) of gain/loss ratings that resulted in a gain overall.",
+        json_schema_extra={"x-unit_measurement": "percent", "x-frontend_multiply": 100},
+    )
+    overall_avg_return_percentile: Optional[float] = Field(
+        default=None,
+        description="The percentile (normalized) of this analyst's overall average"
+        + " return per rating in comparison to other analysts' overall average returns per rating.",
+        json_schema_extra={"x-unit_measurement": "percent", "x-frontend_multiply": 100},
+    )
+    total_ratings_percentile: Optional[float] = Field(
+        default=None,
+        description="The percentile (normalized) of this analyst's total number of ratings"
+        + " in comparison to the total number of ratings published by all other analysts",
+        json_schema_extra={"x-unit_measurement": "percent", "x-frontend_multiply": 100},
+    )
+    total_ratings: Optional[int] = Field(
+        default=None,
+        description="Number of recommendations made by this analyst.",
+    )
+    overall_gain_count: Optional[int] = Field(
+        default=None,
+        description="The number of ratings that have gained value since the date of recommendation",
+    )
+    overall_loss_count: Optional[int] = Field(
+        default=None,
+        description="The number of ratings that have lost value since the date of recommendation",
+    )
+    overall_average_return: Optional[float] = Field(
+        default=None,
+        description="The average percent (normalized) price difference per rating since the date of recommendation",
+        json_schema_extra={"x-unit_measurement": "percent", "x-frontend_multiply": 100},
+    )
+    overall_std_dev: Optional[float] = Field(
+        default=None,
+        description="The standard deviation in percent (normalized) price difference in the"
+        + " analyst's ratings since the date of recommendation",
+        json_schema_extra={"x-unit_measurement": "percent", "x-frontend_multiply": 100},
+    )
+    gain_count_1m: Optional[int] = Field(
+        default=None,
+        description="The number of ratings that have gained value over the last month",
+    )
+    loss_count_1m: Optional[int] = Field(
+        default=None,
+        description="The number of ratings that have lost value over the last month",
+    )
+    average_return_1m: Optional[float] = Field(
+        default=None,
+        description="The average percent (normalized) price difference per rating over the last month",
+        json_schema_extra={"x-unit_measurement": "percent", "x-frontend_multiply": 100},
+    )
+    std_dev_1m: Optional[float] = Field(
+        default=None,
+        description="The standard deviation in percent (normalized) price difference in the"
+        + " analyst's ratings over the last month",
+        json_schema_extra={"x-unit_measurement": "percent", "x-frontend_multiply": 100},
+    )
+    smart_score_1m: Optional[float] = Field(
+        default=None,
+        description="A weighted average smart score over the last month.",
+    )
+    success_rate_1m: Optional[float] = Field(
+        default=None,
+        description="The percentage (normalized) of gain/loss ratings that resulted in a gain over the last month",
+        json_schema_extra={"x-unit_measurement": "percent", "x-frontend_multiply": 100},
+    )
+    gain_count_3m: Optional[int] = Field(
+        default=None,
+        description="The number of ratings that have gained value over the last 3 months",
+    )
+    loss_count_3m: Optional[int] = Field(
+        default=None,
+        description="The number of ratings that have lost value over the last 3 months",
+    )
+    average_return_3m: Optional[float] = Field(
+        default=None,
+        description="The average percent (normalized) price difference per rating over"
+        + " the last 3 months",
+        json_schema_extra={"x-unit_measurement": "percent", "x-frontend_multiply": 100},
+    )
+    std_dev_3m: Optional[float] = Field(
+        default=None,
+        description="The standard deviation in percent (normalized) price difference in the"
+        + " analyst's ratings over the last 3 months",
+        json_schema_extra={"x-unit_measurement": "percent", "x-frontend_multiply": 100},
+    )
+    smart_score_3m: Optional[float] = Field(
+        default=None,
+        description="A weighted average smart score over the last 3 months.",
+    )
+    success_rate_3m: Optional[float] = Field(
+        default=None,
+        description="The percentage (normalized) of gain/loss ratings that resulted in a gain over the last 3 months",
+        json_schema_extra={"x-unit_measurement": "percent", "x-frontend_multiply": 100},
+    )
+    gain_count_6m: Optional[int] = Field(
+        default=None,
+        description="The number of ratings that have gained value over the last 6 months",
+    )
+    loss_count_6m: Optional[int] = Field(
+        default=None,
+        description="The number of ratings that have lost value over the last 6 months",
+    )
+    average_return_6m: Optional[float] = Field(
+        default=None,
+        description="The average percent (normalized) price difference per rating over"
+        + " the last 6 months",
+        json_schema_extra={"x-unit_measurement": "percent", "x-frontend_multiply": 100},
+    )
+    std_dev_6m: Optional[float] = Field(
+        default=None,
+        description="The standard deviation in percent (normalized) price difference in the"
+        + " analyst's ratings over the last 6 months",
+        json_schema_extra={"x-unit_measurement": "percent", "x-frontend_multiply": 100},
+    )
+    gain_count_9m: Optional[int] = Field(
+        default=None,
+        description="The number of ratings that have gained value over the last 9 months",
+    )
+    loss_count_9m: Optional[int] = Field(
+        default=None,
+        description="The number of ratings that have lost value over the last 9 months",
+    )
+    average_return_9m: Optional[float] = Field(
+        default=None,
+        description="The average percent (normalized) price difference per rating over"
+        + " the last 9 months",
+        json_schema_extra={"x-unit_measurement": "percent", "x-frontend_multiply": 100},
+    )
+    std_dev_9m: Optional[float] = Field(
+        default=None,
+        description="The standard deviation in percent (normalized) price difference in the"
+        + " analyst's ratings over the last 9 months",
+        json_schema_extra={"x-unit_measurement": "percent", "x-frontend_multiply": 100},
+    )
+    smart_score_9m: Optional[float] = Field(
+        default=None,
+        description="A weighted average smart score over the last 9 months.",
+    )
+    success_rate_9m: Optional[float] = Field(
+        default=None,
+        description="The percentage (normalized) of gain/loss ratings that resulted in a gain over the last 9 months",
+        json_schema_extra={"x-unit_measurement": "percent", "x-frontend_multiply": 100},
+    )
+    gain_count_1y: Optional[int] = Field(
+        default=None,
+        description="The number of ratings that have gained value over the last 1 year",
+    )
+    loss_count_1y: Optional[int] = Field(
+        default=None,
+        description="The number of ratings that have lost value over the last 1 year",
+    )
+    average_return_1y: Optional[float] = Field(
+        default=None,
+        description="The average percent (normalized) price difference per rating over"
+        + " the last 1 year",
+        json_schema_extra={"x-unit_measurement": "percent", "x-frontend_multiply": 100},
+    )
+    std_dev_1y: Optional[float] = Field(
+        default=None,
+        description="The standard deviation in percent (normalized) price difference in the"
+        + " analyst's ratings over the last 1 year",
+        json_schema_extra={"x-unit_measurement": "percent", "x-frontend_multiply": 100},
+    )
+    smart_score_1y: Optional[float] = Field(
+        default=None,
+        description="A weighted average smart score over the last 1 year.",
+    )
+    success_rate_1y: Optional[float] = Field(
+        default=None,
+        description="The percentage (normalized) of gain/loss ratings that resulted in a gain over the last 1 year",
+        json_schema_extra={"x-unit_measurement": "percent", "x-frontend_multiply": 100},
+    )
+    gain_count_2y: Optional[int] = Field(
+        default=None,
+        description="The number of ratings that have gained value over the last 2 years",
+    )
+    loss_count_2y: Optional[int] = Field(
+        default=None,
+        description="The number of ratings that have lost value over the last 2 years",
+    )
+    average_return_2y: Optional[float] = Field(
+        default=None,
+        description="The average percent (normalized) price difference per rating over"
+        + " the last 2 years",
+        json_schema_extra={"x-unit_measurement": "percent", "x-frontend_multiply": 100},
+    )
+    std_dev_2y: Optional[float] = Field(
+        default=None,
+        description="The standard deviation in percent (normalized) price difference in the"
+        + " analyst's ratings over the last 2 years",
+        json_schema_extra={"x-unit_measurement": "percent", "x-frontend_multiply": 100},
+    )
+    smart_score_2y: Optional[float] = Field(
+        default=None,
+        description="A weighted average smart score over the last 3 years.",
+    )
+    success_rate_2y: Optional[float] = Field(
+        default=None,
+        description="The percentage (normalized) of gain/loss ratings that resulted in a gain over the last 2 years",
+        json_schema_extra={"x-unit_measurement": "percent", "x-frontend_multiply": 100},
+    )
+    gain_count_3y: Optional[int] = Field(
+        default=None,
+        description="The number of ratings that have gained value over the last 3 years",
+    )
+    loss_count_3y: Optional[int] = Field(
+        default=None,
+        description="The number of ratings that have lost value over the last 3 years",
+    )
+    average_return_3y: Optional[float] = Field(
+        default=None,
+        description="The average percent (normalized) price difference per rating over"
+        + " the last 3 years",
+        json_schema_extra={"x-unit_measurement": "percent", "x-frontend_multiply": 100},
+    )
+    std_dev_3y: Optional[float] = Field(
+        default=None,
+        description="The standard deviation in percent (normalized) price difference in the"
+        + " analyst's ratings over the last 3 years",
+        json_schema_extra={"x-unit_measurement": "percent", "x-frontend_multiply": 100},
+    )
+    smart_score_3y: Optional[float] = Field(
+        default=None,
+        description="A weighted average smart score over the last 3 years.",
+    )
+    success_rate_3y: Optional[float] = Field(
+        default=None,
+        description="The percentage (normalized) of gain/loss ratings that resulted in a gain over the last 3 years",
+        json_schema_extra={"x-unit_measurement": "percent", "x-frontend_multiply": 100},
+    )
+
+    @field_validator("last_updated", mode="before", check_fields=False)
+    @classmethod
+    def validate_date(cls, v: float) -> Optional[dateType]:
+        """Validate last_updated."""
+        # pylint: disable=import-outside-toplevel
+        from openbb_core.provider.utils.helpers import safe_fromtimestamp
+
+        if v:
+            dt = safe_fromtimestamp(v, tz=timezone.utc)
+            return dt.date() if dt.time() == dt.min.time() else dt
+        return None
+
+    @model_validator(mode="before")
+    @classmethod
+    def replace_empty_strings(cls, values):
+        """Check for empty strings and replace with None."""
+        return (
+            {k: None if v == "" else v for k, v in values.items()}
+            if isinstance(values, dict)
+            else values
+        )
+
+    @model_validator(mode="before")
+    @classmethod
+    def normalize_percent(cls, values):
+        """Normalize percent values."""
+        contains = ["return", "percentile", "stdev", "rate"]
+        for key in values:
+            if any(x in key for x in contains):
+                values[key] = (
+                    float(values[key]) / 100
+                    if values[key] != "" or values[key] is not None
+                    else None
+                )
+        return values
+
+
+class BenzingaAnalystSearchFetcher(
+    Fetcher[BenzingaAnalystSearchQueryParams, List[BenzingaAnalystSearchData]]
+):
+    """Benzinga Analyst Search Fetcher."""
+
+    @staticmethod
+    def transform_query(params: Dict[str, Any]) -> BenzingaAnalystSearchQueryParams:
+        """Transform query params."""
+        return BenzingaAnalystSearchQueryParams(**params)
+
+    @staticmethod
+    async def aextract_data(
+        query: BenzingaAnalystSearchQueryParams,
+        credentials: Optional[Dict[str, str]],
+        **kwargs: Any,
+    ) -> List[Dict]:
+        """Extract the raw data."""
+        # pylint: disable=import-outside-toplevel
+        from openbb_benzinga.utils.helpers import response_callback
+        from openbb_core.provider.utils.helpers import amake_request, get_querystring
+
+        token = credentials.get("benzinga_api_key") if credentials else ""
+        querystring = get_querystring(query.model_dump(by_alias=True), [])
+        url = f"https://api.benzinga.com/api/v2.1/calendar/ratings/analysts?{querystring}&token={token}"
+        data = await amake_request(url, response_callback=response_callback, **kwargs)
+
+        if (isinstance(data, list) and not data) or (
+            isinstance(data, dict) and not data.get("analyst_ratings_analyst")
+        ):
+            raise EmptyDataError("No ratings data returned.")
+
+        if isinstance(data, dict) and "analyst_ratings_analyst" not in data:
+            raise OpenBBError(
+                f"Unexpected data format. Expected 'analyst_ratings_analyst' key, got: {list(data.keys())}"
+            )
+
+        if not isinstance(data, dict):
+            raise OpenBBError(
+                f"Unexpected data format. Expected dict, got: {type(data).__name__}"
+            )
+
+        return data["analyst_ratings_analyst"]
+
+    @staticmethod
+    def transform_data(
+        query: BenzingaAnalystSearchQueryParams,
+        data: List[Dict],
+        **kwargs: Any,
+    ) -> List[BenzingaAnalystSearchData]:
+        """Transform the data."""
+        results: List[BenzingaAnalystSearchData] = []
+        for item in data:
+            if item.get("firm_id"):
+                result = {
+                    "updated": item.get("updated", None),
+                    "firm_id": item.get("firm_id", None),
+                    "firm_name": item.get("firm_name", None),
+                    "id": item.get("id", None),
+                    "name_first": item.get("name_first", None),
+                    "name_full": item.get("name_full", None),
+                    "name_last": item.get("name_last", None),
+                    **item["ratings_accuracy"],
+                }
+                results.append(BenzingaAnalystSearchData.model_validate(result))
+        return results

openbb_platform/providers/benzinga/openbb_benzinga/models/company_news.py

@@ -0,0 +1,205 @@
+"""Benzinga Company News Model."""
+
+# pylint: disable=unused-argument
+
+from datetime import (
+    date as dateType,
+    datetime,
+)
+from typing import Any, Dict, List, Literal, Optional
+
+from openbb_core.app.model.abstract.error import OpenBBError
+from openbb_core.provider.abstract.fetcher import Fetcher
+from openbb_core.provider.standard_models.company_news import (
+    CompanyNewsData,
+    CompanyNewsQueryParams,
+)
+from openbb_core.provider.utils.descriptions import QUERY_DESCRIPTIONS
+from openbb_core.provider.utils.errors import EmptyDataError, UnauthorizedError
+from pydantic import Field, field_validator
+
+
+class BenzingaCompanyNewsQueryParams(CompanyNewsQueryParams):
+    """Benzinga Company News Query.
+
+    Source: https://docs.benzinga.io/benzinga/newsfeed-v2.html
+    """
+
+    __alias_dict__ = {
+        "symbol": "tickers",
+        "display": "displayOutput",
+        "limit": "pageSize",
+        "start_date": "dateFrom",
+        "end_date": "dateTo",
+        "updated_since": "updatedSince",
+        "published_since": "publishedSince",
+    }
+    __json_schema_extra__ = {"symbol": {"multiple_items_allowed": True}}
+
+    date: Optional[dateType] = Field(
+        default=None, description=QUERY_DESCRIPTIONS.get("date", "")
+    )
+    display: Literal["headline", "abstract", "full"] = Field(
+        default="full",
+        description="Specify headline only (headline), headline + teaser (abstract), or headline + full body (full).",
+    )
+    updated_since: Optional[int] = Field(
+        default=None,
+        description="Number of seconds since the news was updated.",
+    )
+    published_since: Optional[int] = Field(
+        default=None,
+        description="Number of seconds since the news was published.",
+    )
+
+    sort: Literal["id", "created", "updated"] = Field(
+        default="created", description="Key to sort the news by."
+    )
+    order: Literal["asc", "desc"] = Field(
+        default="desc", description="Order to sort the news by."
+    )
+    isin: Optional[str] = Field(default=None, description="The company's ISIN.")
+    cusip: Optional[str] = Field(default=None, description="The company's CUSIP.")
+    channels: Optional[str] = Field(
+        default=None, description="Channels of the news to retrieve."
+    )
+    topics: Optional[str] = Field(
+        default=None, description="Topics of the news to retrieve."
+    )
+    authors: Optional[str] = Field(
+        default=None, description="Authors of the news to retrieve."
+    )
+    content_types: Optional[str] = Field(
+        default=None, description="Content types of the news to retrieve."
+    )
+
+
+class BenzingaCompanyNewsData(CompanyNewsData):
+    """Benzinga Company News Data."""
+
+    __alias_dict__ = {
+        "symbols": "stocks",
+        "date": "created",
+        "text": "body",
+        "images": "image",
+    }
+
+    id: str = Field(description="Article ID.")
+    author: Optional[str] = Field(default=None, description="Author of the article.")
+    teaser: Optional[str] = Field(description="Teaser of the news.", default=None)
+    images: Optional[List[Dict[str, str]]] = Field(
+        default=None, description="URL to the images of the news."
+    )
+    channels: Optional[str] = Field(
+        default=None,
+        description="Channels associated with the news.",
+    )
+    stocks: Optional[str] = Field(
+        description="Stocks associated with the news.",
+        default=None,
+    )
+    tags: Optional[str] = Field(
+        description="Tags associated with the news.",
+        default=None,
+    )
+    updated: Optional[datetime] = Field(
+        default=None, description="Updated date of the news."
+    )
+
+    @field_validator("symbols", mode="before", check_fields=False)
+    @classmethod
+    def symbols_string(cls, v):
+        """Symbols string validator."""
+        return ",".join([item["name"] for item in v])
+
+    @field_validator("date", "updated", mode="before", check_fields=False)
+    def date_validate(cls, v):  # pylint: disable=E0213
+        """Return the date as a datetime object."""
+        return datetime.strptime(v, "%a, %d %b %Y %H:%M:%S %z")
+
+    @field_validator("stocks", "channels", "tags", mode="before", check_fields=False)
+    def list_validate(cls, v):  # pylint: disable=E0213
+        """Return the list as a string."""
+        return ",".join(
+            [item.get("name", None) for item in v if item.get("name", None)]
+        )
+
+    @field_validator("id", mode="before", check_fields=False)
+    def id_validate(cls, v):  # pylint: disable=E0213
+        """Return the id as a string."""
+        return str(v)
+
+
+class BenzingaCompanyNewsFetcher(
+    Fetcher[
+        BenzingaCompanyNewsQueryParams,
+        List[BenzingaCompanyNewsData],
+    ]
+):
+    """Transform the query, extract and transform the data from the Benzinga endpoints."""
+
+    @staticmethod
+    def transform_query(params: Dict[str, Any]) -> BenzingaCompanyNewsQueryParams:
+        """Transform query params."""
+        return BenzingaCompanyNewsQueryParams(**params)
+
+    @staticmethod
+    async def aextract_data(
+        query: BenzingaCompanyNewsQueryParams,
+        credentials: Optional[Dict[str, str]],
+        **kwargs: Any,
+    ) -> List[Dict]:
+        """Extract data."""
+        # pylint: disable=import-outside-toplevel
+        import asyncio  # noqa
+        import math
+        from openbb_core.provider.utils.helpers import amake_request, get_querystring
+        from openbb_benzinga.utils.helpers import response_callback
+
+        token = credentials.get("benzinga_api_key") if credentials else ""
+
+        base_url = "https://api.benzinga.com/api/v2/news"
+
+        model = query.model_dump(by_alias=True)
+        model["sort"] = (
+            f"{query.sort}:{query.order}" if query.sort and query.order else ""
+        )
+        querystring = get_querystring(model, ["order", "pageSize"])
+
+        pages = math.ceil(query.limit / 100) if query.limit else 1
+        page_size = 100 if query.limit and query.limit > 100 else query.limit
+        urls = [
+            f"{base_url}?{querystring}&page={page}&pageSize={page_size}&token={token}"
+            for page in range(pages)
+        ]
+
+        results: list = []
+
+        async def get_one(url):
+            """Get data for one url."""
+            try:
+                response = await amake_request(
+                    url, response_callback=response_callback, **kwargs
+                )
+                if response:
+                    results.extend(response)
+            except (OpenBBError, UnauthorizedError) as e:
+                raise e from e
+
+        await asyncio.gather(*[get_one(url) for url in urls])
+
+        if not results:
+            raise EmptyDataError("The request was returned empty.")
+
+        return sorted(
+            results, key=lambda x: x.get("created"), reverse=query.order == "desc"
+        )[: query.limit if query.limit else len(results)]
+
+    @staticmethod
+    def transform_data(
+        query: BenzingaCompanyNewsQueryParams,
+        data: List[Dict],
+        **kwargs: Any,
+    ) -> List[BenzingaCompanyNewsData]:
+        """Transform data."""
+        return [BenzingaCompanyNewsData.model_validate(item) for item in data]

openbb_platform/providers/benzinga/openbb_benzinga/models/price_target.py

@@ -0,0 +1,318 @@
+"""Benzinga Price Target Model."""
+
+# pylint: disable=unused-argument
+
+from datetime import (
+    date as dateType,
+    datetime,
+    time,
+    timezone,
+)
+from typing import Any, Dict, List, Literal, Optional, Union
+
+from openbb_core.app.model.abstract.error import OpenBBError
+from openbb_core.provider.abstract.fetcher import Fetcher
+from openbb_core.provider.standard_models.price_target import (
+    PriceTargetData,
+    PriceTargetQueryParams,
+)
+from openbb_core.provider.utils.descriptions import QUERY_DESCRIPTIONS
+from openbb_core.provider.utils.errors import EmptyDataError
+from pydantic import Field, field_validator, model_validator
+
+COVERAGE_DICT = {
+    "downgrades": "Downgrades",
+    "maintains": "Maintains",
+    "reinstates": "Reinstates",
+    "reiterates": "Reiterates",
+    "upgrades": "Upgrades",
+    "assumes": "Assumes",
+    "initiates": "Initiates Coverage On",
+    "terminates": "Terminates Coverage On",
+    "removes": "Removes",
+    "suspends": "Suspends",
+    "firm_dissolved": "Firm Dissolved",
+}
+
+
+class BenzingaPriceTargetQueryParams(PriceTargetQueryParams):
+    """Benzinga Price Target Query.
+
+    Source: https://docs.benzinga.io/benzinga-apis/calendar/get-ratings
+    """
+
+    __alias_dict__ = {
+        "limit": "pagesize",
+        "symbol": "parameters[tickers]",
+        "date": "parameters[date]",
+        "start_date": "parameters[date_from]",
+        "end_date": "parameters[date_to]",
+        "updated": "parameters[updated]",
+        "importance": "parameters[importance]",
+        "action": "parameters[action]",
+        "analyst_ids": "parameters[analyst_id]",
+        "firm_ids": "parameters[firm_id]",
+    }
+    __json_schema_extra__ = {
+        "symbol": {"multiple_items_allowed": True},
+        "analyst_ids": {"multiple_items_allowed": True},
+        "firm_ids": {"multiple_items_allowed": True},
+        "fields": {"multiple_items_allowed": True},
+        "action": {
+            "multiple_items_allowed": False,
+            "choices": [
+                "downgrades",
+                "maintains",
+                "reinstates",
+                "reiterates",
+                "upgrades",
+                "assumes",
+                "initiates",
+                "terminates",
+                "removes",
+                "suspends",
+                "firm_dissolved",
+            ],
+        },
+    }
+
+    page: Optional[int] = Field(
+        default=0,
+        description="Page offset. For optimization, performance and technical reasons,"
+        + " page offsets are limited from 0 - 100000. Limit the query results by other parameters such as date."
+        + " Used in conjunction with the limit and date parameters.",
+    )
+    date: Optional[dateType] = Field(
+        default=None,
+        description="Date for calendar data, shorthand for date_from and date_to.",
+    )
+    start_date: Optional[dateType] = Field(
+        default=None,
+        description=QUERY_DESCRIPTIONS.get("start_date", ""),
+    )
+    end_date: Optional[dateType] = Field(
+        default=None,
+        description=QUERY_DESCRIPTIONS.get("end_date", ""),
+    )
+    updated: Optional[Union[dateType, int]] = Field(
+        default=None,
+        description="Records last Updated Unix timestamp (UTC)."
+        + " This will force the sort order to be Greater Than or Equal to the timestamp indicated."
+        + " The date can be a date string or a Unix timestamp."
+        + " The date string must be in the format of YYYY-MM-DD.",
+    )
+    importance: Optional[int] = Field(
+        default=None,
+        description="Importance level to filter by."
+        + " Uses Greater Than or Equal To the importance indicated",
+    )
+    action: Optional[
+        Literal[
+            "downgrades",
+            "maintains",
+            "reinstates",
+            "reiterates",
+            "upgrades",
+            "assumes",
+            "initiates",
+            "terminates",
+            "removes",
+            "suspends",
+            "firm_dissolved",
+        ]
+    ] = Field(
+        default=None,
+        description="Filter by a specific action_company.",
+    )
+    analyst_ids: Optional[Union[List[str], str]] = Field(
+        default=None,
+        description="Comma-separated list of analyst (person) IDs."
+        + " Omitting will bring back all available analysts.",
+    )
+    firm_ids: Optional[Union[List[str], str]] = Field(
+        default=None,
+        description="Comma-separated list of firm IDs.",
+    )
+    fields: Optional[Union[List[str], str]] = Field(
+        default=None,
+        description="Comma-separated list of fields to include in the response."
+        " See https://docs.benzinga.io/benzinga-apis/calendar/get-ratings to learn about the available fields.",
+    )
+
+    @field_validator("action", mode="after", check_fields=False)
+    @classmethod
+    def convert_action(cls, v):
+        """Convert to the action string."""
+        return COVERAGE_DICT[v] if v else None
+
+    @field_validator("updated", mode="after", check_fields=False)
+    @classmethod
+    def date_validate(cls, v):
+        """Convert the the dates to a standard format."""
+        if isinstance(v, datetime):
+            v = v.replace(tzinfo=timezone.utc)
+            return int(v.timestamp())
+        if isinstance(v, dateType):
+            v = datetime.combine(v, time(), tzinfo=timezone.utc)
+            return int(v.timestamp())
+        return None
+
+    @field_validator(
+        "fields", "firm_ids", "analyst_ids", mode="before", check_fields=False
+    )
+    @classmethod
+    def convert_list(cls, v: Union[str, List[str]]):
+        """Convert a List[str] to a string list."""
+        if isinstance(v, str):
+            return v
+        return ",".join(v) if v else None
+
+
+class BenzingaPriceTargetData(PriceTargetData):
+    """Benzinga Price Target Data."""
+
+    __alias_dict__ = {
+        "symbol": "ticker",
+        "published_date": "date",
+        "adj_price_target": "adjusted_pt_current",
+        "price_target": "pt_current",
+        "price_target_previous": "pt_prior",
+        "previous_adj_price_target": "adjusted_pt_prior",
+        "published_time": "time",
+        "analyst_firm": "analyst",
+        "company_name": "name",
+        "rating_previous": "rating_prior",
+        "url_analyst": "url",
+        "action": "action_company",
+        "action_change": "action_pt",
+        "last_updated": "updated",
+    }
+
+    action: Optional[
+        Literal[
+            "Downgrades",
+            "Maintains",
+            "Reinstates",
+            "Reiterates",
+            "Upgrades",
+            "Assumes",
+            "Initiates Coverage On",
+            "Terminates Coverage On",
+            "Removes",
+            "Suspends",
+            "Firm Dissolved",
+        ]
+    ] = Field(
+        default=None,
+        description="Description of the change in rating from firm's last rating."
+        "Note that all of these terms are precisely defined.",
+    )
+    action_change: Optional[
+        Literal["Announces", "Maintains", "Lowers", "Raises", "Removes", "Adjusts"]
+    ] = Field(
+        default=None,
+        description="Description of the change in price target from firm's last price target.",
+    )
+    importance: Optional[Literal[0, 1, 2, 3, 4, 5]] = Field(
+        default=None,
+        description="Subjective Basis of How Important Event is to Market. 5 = High",
+    )
+    notes: Optional[str] = Field(default=None, description="Notes of the price target.")
+    analyst_id: Optional[str] = Field(default=None, description="Id of the analyst.")
+    url_news: Optional[str] = Field(
+        default=None,
+        description="URL for analyst ratings news articles for this ticker on Benzinga.com.",
+    )
+    url_analyst: Optional[str] = Field(
+        default=None,
+        description="URL for analyst ratings page for this ticker on Benzinga.com.",
+    )
+    id: Optional[str] = Field(default=None, description="Unique ID of this entry.")
+    last_updated: Optional[datetime] = Field(
+        default=None,
+        description="Last updated timestamp, UTC.",
+    )
+
+    @field_validator("published_date", mode="before", check_fields=False)
+    @classmethod
+    def parse_date(cls, v: str):
+        """Parse the publisihed_date."""
+        return datetime.strptime(v, "%Y-%m-%d").date() if v else None
+
+    @field_validator("last_updated", mode="before", check_fields=False)
+    @classmethod
+    def validate_date(cls, v: float) -> Optional[dateType]:
+        """Convert the Unix timestamp to a datetime object."""
+        # pylint: disable=import-outside-toplevel
+        from openbb_core.provider.utils.helpers import safe_fromtimestamp
+
+        if v:
+            dt = safe_fromtimestamp(v, tz=timezone.utc)
+            return dt.date() if dt.time() == dt.min.time() else dt
+        return None
+
+    @model_validator(mode="before")
+    @classmethod
+    def replace_empty_strings(cls, values):
+        """Check for empty strings and replace with None."""
+        return {k: None if v == "" else v for k, v in values.items()}
+
+
+class BenzingaPriceTargetFetcher(
+    Fetcher[
+        BenzingaPriceTargetQueryParams,
+        List[BenzingaPriceTargetData],
+    ]
+):
+    """Transform the query, extract and transform the data from the Benzinga endpoints."""
+
+    @staticmethod
+    def transform_query(params: Dict[str, Any]) -> BenzingaPriceTargetQueryParams:
+        """Transform the query params."""
+        return BenzingaPriceTargetQueryParams(**params)
+
+    @staticmethod
+    async def aextract_data(
+        query: BenzingaPriceTargetQueryParams,
+        credentials: Optional[Dict[str, str]],
+        **kwargs: Any,
+    ) -> List[Dict]:
+        """Return the raw data from the Benzinga endpoint."""
+        # pylint: disable=import-outside-toplevel
+        from openbb_benzinga.utils.helpers import response_callback
+        from openbb_core.provider.utils.helpers import amake_request, get_querystring
+
+        token = credentials.get("benzinga_api_key") if credentials else ""
+
+        base_url = "https://api.benzinga.com/api/v2.1/calendar/ratings"
+        querystring = get_querystring(query.model_dump(by_alias=True), [])
+
+        url = f"{base_url}?{querystring}&token={token}"
+        data = await amake_request(url, response_callback=response_callback, **kwargs)
+
+        if isinstance(data, dict) and "ratings" not in data:
+            raise OpenBBError(
+                f"Unexpected data format. Expected 'ratings' key, got: {list(data.keys())}"
+            )
+        if not isinstance(data, dict):
+            raise OpenBBError(
+                f"Unexpected data format. Expected dict, got: {type(data)}"
+            )
+        if isinstance(data, dict) and not data.get("ratings"):
+            raise EmptyDataError("No ratings data returned.")
+
+        return data["ratings"]
+
+    @staticmethod
+    def transform_data(
+        query: BenzingaPriceTargetQueryParams,
+        data: List[Dict],
+        **kwargs: Any,
+    ) -> List[BenzingaPriceTargetData]:
+        """Return the transformed data."""
+        results: List[BenzingaPriceTargetData] = []
+        # Remove duplicated field with a URL
+        for item in data:
+            item.pop("url_calendar", None)
+            results.append(BenzingaPriceTargetData.model_validate(item))
+        return results

openbb_platform/providers/benzinga/openbb_benzinga/models/world_news.py

@@ -0,0 +1,197 @@
+"""Benzinga World News Model."""
+
+# pylint: disable=unused-argument
+
+from datetime import (
+    date as dateType,
+    datetime,
+)
+from typing import Any, Dict, List, Literal, Optional
+
+from openbb_core.app.model.abstract.error import OpenBBError
+from openbb_core.provider.abstract.fetcher import Fetcher
+from openbb_core.provider.standard_models.world_news import (
+    WorldNewsData,
+    WorldNewsQueryParams,
+)
+from openbb_core.provider.utils.descriptions import QUERY_DESCRIPTIONS
+from openbb_core.provider.utils.errors import EmptyDataError, UnauthorizedError
+from pydantic import Field, field_validator
+
+
+class BenzingaWorldNewsQueryParams(WorldNewsQueryParams):
+    """Benzinga World News Query.
+
+    Source: https://docs.benzinga.io/benzinga/newsfeed-v2.html
+    """
+
+    __alias_dict__ = {
+        "display": "displayOutput",
+        "limit": "pageSize",
+        "start_date": "dateFrom",
+        "end_date": "dateTo",
+        "updated_since": "updatedSince",
+        "published_since": "publishedSince",
+    }
+    date: Optional[dateType] = Field(
+        default=None, description=QUERY_DESCRIPTIONS.get("date", "")
+    )
+    display: Literal["headline", "abstract", "full"] = Field(
+        default="full",
+        description="Specify headline only (headline), headline + teaser (abstract), or headline + full body (full).",
+    )
+    updated_since: Optional[int] = Field(
+        default=None,
+        description="Number of seconds since the news was updated.",
+    )
+    published_since: Optional[int] = Field(
+        default=None,
+        description="Number of seconds since the news was published.",
+    )
+    sort: Literal["id", "created", "updated"] = Field(
+        default="created", description="Key to sort the news by."
+    )
+    order: Literal["asc", "desc"] = Field(
+        default="desc", description="Order to sort the news by."
+    )
+    isin: Optional[str] = Field(
+        default=None, description="The ISIN of the news to retrieve."
+    )
+    cusip: Optional[str] = Field(
+        default=None, description="The CUSIP of the news to retrieve."
+    )
+    channels: Optional[str] = Field(
+        default=None, description="Channels of the news to retrieve."
+    )
+    topics: Optional[str] = Field(
+        default=None, description="Topics of the news to retrieve."
+    )
+    authors: Optional[str] = Field(
+        default=None, description="Authors of the news to retrieve."
+    )
+    content_types: Optional[str] = Field(
+        default=None, description="Content types of the news to retrieve."
+    )
+
+
+class BenzingaWorldNewsData(WorldNewsData):
+    """Benzinga World News Data."""
+
+    __alias_dict__ = {"date": "created", "text": "body", "images": "image"}
+
+    id: str = Field(description="Article ID.")
+    author: Optional[str] = Field(default=None, description="Author of the news.")
+    teaser: Optional[str] = Field(description="Teaser of the news.", default=None)
+    channels: Optional[str] = Field(
+        default=None,
+        description="Channels associated with the news.",
+    )
+    stocks: Optional[str] = Field(
+        description="Stocks associated with the news.",
+        default=None,
+    )
+    tags: Optional[str] = Field(
+        description="Tags associated with the news.",
+        default=None,
+    )
+    updated: Optional[datetime] = Field(
+        default=None, description="Updated date of the news."
+    )
+
+    @field_validator("date", "updated", mode="before", check_fields=False)
+    @classmethod
+    def date_validate(cls, v):
+        """Return the date as a datetime object."""
+        return datetime.strptime(v, "%a, %d %b %Y %H:%M:%S %z")
+
+    @field_validator("stocks", "channels", "tags", mode="before", check_fields=False)
+    @classmethod
+    def list_validate(cls, v):
+        """Return the list as a string."""
+        v = ",".join([item.get("name", None) for item in v if item.get("name", None)])
+        return v if v != "" else None
+
+    @field_validator(
+        "id", "text", "teaser", "title", "author", mode="before", check_fields=False
+    )
+    @classmethod
+    def id_validate(cls, v):
+        """Return the a string if the field is not empty."""
+        return str(v) if v else None
+
+    @field_validator("images", mode="before", check_fields=False)
+    @classmethod
+    def empty_list(cls, v):
+        """Return None instead of []"""
+        return None if v == [] else v
+
+
+class BenzingaWorldNewsFetcher(
+    Fetcher[
+        BenzingaWorldNewsQueryParams,
+        List[BenzingaWorldNewsData],
+    ]
+):
+    """Transform the query, extract and transform the data from the Benzinga endpoints."""
+
+    @staticmethod
+    def transform_query(params: Dict[str, Any]) -> BenzingaWorldNewsQueryParams:
+        """Transform the query parameters."""
+        return BenzingaWorldNewsQueryParams(**params)
+
+    @staticmethod
+    async def aextract_data(
+        query: BenzingaWorldNewsQueryParams,
+        credentials: Optional[Dict[str, str]],
+        **kwargs: Any,
+    ) -> List[Dict]:
+        """Extract the data."""
+        # pylint: disable=import-outside-toplevel
+        import asyncio  # noqa
+        import math
+        from openbb_core.provider.utils.helpers import amake_request, get_querystring
+        from openbb_benzinga.utils.helpers import response_callback
+
+        token = credentials.get("benzinga_api_key") if credentials else ""
+        base_url = "https://api.benzinga.com/api/v2/news"
+
+        query = query.model_copy(update={"sort": f"{query.sort}:{query.order}"})
+        querystring = get_querystring(query.model_dump(by_alias=True), ["order"])
+
+        pages = math.ceil(query.limit / 100)
+
+        urls = [
+            f"{base_url}?{querystring}&page={page}&token={token}"
+            for page in range(pages)
+        ]
+
+        results: list = []
+
+        async def get_one(url):
+            """Get data for one url."""
+            try:
+                response = await amake_request(
+                    url, response_callback=response_callback, **kwargs
+                )
+                if response:
+                    results.extend(response)
+            except (OpenBBError, UnauthorizedError) as e:
+                raise e from e
+
+        await asyncio.gather(*[get_one(url) for url in urls])
+
+        if not results:
+            raise EmptyDataError("The request was returned empty.")
+
+        return sorted(
+            results, key=lambda x: x.get("created"), reverse=query.order == "desc"
+        )[: query.limit if query.limit else len(results)]
+
+    @staticmethod
+    def transform_data(
+        query: BenzingaWorldNewsQueryParams,
+        data: List[Dict],
+        **kwargs: Any,
+    ) -> List[BenzingaWorldNewsData]:
+        """Transform the data."""
+        return [BenzingaWorldNewsData.model_validate(item) for item in data]

openbb_platform/providers/benzinga/openbb_benzinga/utils/__init__.py

@@ -0,0 +1 @@
+"""Benzinga Provider Utils."""

openbb_platform/providers/benzinga/openbb_benzinga/utils/helpers.py

@@ -0,0 +1,24 @@
+"""Benzinga Helpers."""
+
+from openbb_core.app.model.abstract.error import OpenBBError
+from openbb_core.provider.utils.errors import EmptyDataError, UnauthorizedError
+
+
+async def response_callback(response, _):
+    """Response callback."""
+    # pylint: disable=import-outside-toplevel
+    results = await response.json()
+    if (
+        results
+        and isinstance(results, list)
+        and len(results) == 1
+        and isinstance(results[0], str)
+    ):
+        if "access denied" in results[0].lower():
+            raise UnauthorizedError(f"Unauthorized Benzinga request -> {results[0]}")
+        raise OpenBBError(results[0])
+
+    if isinstance(results, list) and not results:
+        raise EmptyDataError("The request was returned empty.")
+
+    return results

openbb_platform/providers/benzinga/pyproject.toml

@@ -0,0 +1,19 @@
+[tool.poetry]
+name = "openbb-benzinga"
+version = "1.4.1"
+description = "Benzinga extension for OpenBB"
+authors = ["OpenBB Team <hello@openbb.co>"]
+license = "AGPL-3.0-only"
+readme = "README.md"
+packages = [{ include = "openbb_benzinga" }]
+
+[tool.poetry.dependencies]
+python = ">=3.9.21,<3.13"
+openbb-core = "^1.4.6"
+
+[build-system]
+requires = ["poetry-core"]
+build-backend = "poetry.core.masonry.api"
+
+[tool.poetry.plugins."openbb_provider_extension"]
+benzinga = "openbb_benzinga:benzinga_provider"

openbb_platform/providers/benzinga/tests/__init__.py

@@ -0,0 +1 @@
+"""Test Benzinga fetchers."""

openbb_platform/providers/benzinga/tests/record/http/test_benzinga_fetchers/test_benzinga_analyst_search_fetcher_urllib3_v1.yaml

@@ -0,0 +1,282 @@
+interactions:
+- request:
+    body: null
+    headers:
+      Accept:
+      - application/json
+      Accept-Encoding:
+      - gzip, deflate
+      Connection:
+      - keep-alive
+    method: GET
+    uri: https://api.benzinga.com/api/v2.1/calendar/ratings/analysts?firm_name=Barclays&page=0&pageSize=100&token=MOCK_TOKEN
+  response:
+    body:
+      string: !!binary |
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+    headers:
+      Connection:
+      - keep-alive
+      Content-Encoding:
+      - gzip
+      Content-Type:
+      - application/json; charset=utf-8
+      Date:
+      - Fri, 16 Feb 2024 20:32:34 GMT
+      Transfer-Encoding:
+      - chunked
+      Vary:
+      - Accept-Encoding
+      Via:
+      - kong/2.4.1, 1.1 9adef5b1c5fc9ca80d6f4f8d19e103a2.cloudfront.net (CloudFront)
+      X-Amz-Cf-Id:
+      - wzPB7RswTYmBQtCmdpuOoCBrs9caz6DluhsLZXglRNPo13Tc9phzyA==
+      X-Amz-Cf-Pop:
+      - SEA19-C3
+      X-Bz-Request-Id:
+      - bBEB7mxrS7rediVwPHqUVe
+      X-Cache:
+      - Miss from cloudfront
+      X-Kong-Proxy-Latency:
+      - '0'
+      X-Kong-Upstream-Latency:
+      - '35'
+      X-Powered-By:
+      - Athlon 64 X2
+    status:
+      code: 200
+      message: OK
+version: 1

openbb_platform/providers/benzinga/tests/record/http/test_benzinga_fetchers/test_benzinga_analyst_search_fetcher_urllib3_v2.yaml

@@ -0,0 +1,311 @@
+interactions:
+- request:
+    body: null
+    headers:
+      Accept:
+      - application/json
+      Accept-Encoding:
+      - gzip, deflate
+      Connection:
+      - keep-alive
+    method: GET
+    uri: https://api.benzinga.com/api/v2.1/calendar/ratings/analysts?firm_name=Barclays&page=0&pageSize=100&token=MOCK_TOKEN
+  response:
+    body:
+      string: !!binary |
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+    headers:
+      Connection:
+      - keep-alive
+      Content-Encoding:
+      - gzip
+      Content-Type:
+      - application/json; charset=utf-8
+      Date:
+      - Thu, 27 Jun 2024 10:11:58 GMT
+      Transfer-Encoding:
+      - chunked
+      Vary:
+      - Accept-Encoding
+      Via:
+      - kong/3.5.0, 1.1 80870c148d8c8f3b510fdacf10500460.cloudfront.net (CloudFront)
+      X-Amz-Cf-Id:
+      - 5W8ENYwzyPIYamcaVve42r-OoINosG4-nd-RFJh3yd3rv0Cz6CVxUQ==
+      X-Amz-Cf-Pop:
+      - AMS58-P1
+      X-Bz-Request-Id:
+      - ZOByrHQqbXbOFBCngttzZT
+      X-Cache:
+      - Miss from cloudfront
+      X-Kong-Proxy-Latency:
+      - '0'
+      X-Kong-Request-Id:
+      - 080a6a0f8f719e2942169b49316ca76b
+      X-Kong-Upstream-Latency:
+      - '36'
+      X-Powered-By:
+      - Athlon 64 X2
+    status:
+      code: 200
+      message: OK
+version: 1

openbb_platform/providers/benzinga/tests/record/http/test_benzinga_fetchers/test_benzinga_price_target_fetcher_urllib3_v1.yaml

@@ -0,0 +1,229 @@
+interactions:
+- request:
+    body: null
+    headers:
+      Accept:
+      - application/json
+      Accept-Encoding:
+      - gzip, deflate
+      Connection:
+      - keep-alive
+    method: GET
+    uri: https://api.benzinga.com/api/v2.1/calendar/ratings?page=0&pagesize=200&parameters%5Btickers%5D=AAPL&token=MOCK_TOKEN
+  response:
+    body:
+      string: !!binary |
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+      - gzip
+      Content-Type:
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+      Date:
+      - Fri, 16 Feb 2024 19:52:20 GMT
+      Transfer-Encoding:
+      - chunked
+      Vary:
+      - Accept-Encoding
+      Via:
+      - kong/2.4.1, 1.1 0906d4887f6625f4a4467d8d4fd268d2.cloudfront.net (CloudFront)
+      X-Amz-Cf-Id:
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+      - SEA19-C3
+      X-Bz-Request-Id:
+      - w44XRYJcNVDLtWZCdKXWlD
+      X-Cache:
+      - Miss from cloudfront
+      X-Kong-Proxy-Latency:
+      - '0'
+      X-Kong-Upstream-Latency:
+      - '43'
+      X-Powered-By:
+      - Athlon 64 X2
+    status:
+      code: 200
+      message: OK
+version: 1

openbb_platform/providers/benzinga/tests/record/http/test_benzinga_fetchers/test_benzinga_price_target_fetcher_urllib3_v2.yaml

@@ -0,0 +1,230 @@
+interactions:
+- request:
+    body: null
+    headers:
+      Accept:
+      - application/json
+      Accept-Encoding:
+      - gzip, deflate
+      Connection:
+      - keep-alive
+    method: GET
+    uri: https://api.benzinga.com/api/v2.1/calendar/ratings?page=0&pagesize=200&parameters%5Btickers%5D=AAPL&token=MOCK_TOKEN
+  response:
+    body:
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openbb_platform/providers/benzinga/tests/record/http/test_benzinga_fetchers/test_benzinga_world_news_fetcher_urllib3_v2.yaml

@@ -0,0 +1,450 @@
+interactions:
+- request:
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+    headers:
+      Accept:
+      - application/json
+      Accept-Encoding:
+      - gzip, deflate
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+      - keep-alive
+    method: GET
+    uri: https://api.benzinga.com/api/v2/news?displayOutput=full&page=0&pageSize=20&sort=created%3Adesc&token=MOCK_TOKEN
+  response:
+    body:
+      string: "[{\"id\":39519753,\"author\":\"Benzinga Newsdesk\",\"created\":\"Thu,
+        27 Jun 2024 06:11:23 -0400\",\"updated\":\"Thu, 27 Jun 2024 06:11:24 -0400\",\"title\":\"JinkoSolar
+        Has Repurchased 4.5M ADSs In An Aggregate Amount Of Approximately $110.7M
+        In The Open Market Under Its Share Repurchase Program Announced In July 2022
+        And The Extended Share Repurchase Program Announced In December 2023\",\"teaser\":\"\",\"body\":\"\",\"url\":\"https://www.benzinga.com/news/24/06/39519753/jinkosolar-has-repurchased-4-5m-adss-in-an-aggregate-amount-of-approximately-110-7m-in-the-open-mark\",\"image\":[],\"channels\":[{\"name\":\"News\"},{\"name\":\"Commodities\"},{\"name\":\"Buybacks\"},{\"name\":\"Markets\"},{\"name\":\"General\"}],\"stocks\":[{\"name\":\"JKS\"}],\"tags\":[]},{\"id\":39519696,\"author\":\"Benzinga
+        Neuro\",\"created\":\"Thu, 27 Jun 2024 06:09:18 -0400\",\"updated\":\"Thu,
+        27 Jun 2024 06:09:19 -0400\",\"title\":\"Fundstrat's Tom Lee Predicts S&P
+        500 Will Hit 15,000 By 2030 Driven By Gen Z And AI Wave\",\"teaser\":\"Tom
+        Lee, the managing partner and head of research at Fundstrat Global Advisors,
+        shared his bullish prediction for the S&P 500, foreseeing it reaching
+        15,000 by 2030.\",\"body\":\"<p><strong>Tom Lee</strong>, the managing partner
+        and head of research at<strong> Fundstrat Global Advisors</strong>, shared
+        his <a href=\\\"https://www.benzinga.com/analyst-ratings/analyst-color/24/06/39350137/s-p-500-poised-to-extend-bull-run-market-strategist-sees-ai-fervor-and-ebbing-infla\\\">bullish
+        prediction</a> for the S&amp;P 500, foreseeing it reaching 15,000 by 2030
+        riding the AI wave.</p>\\n\\n\\n\\n<p><strong>What Happened</strong>: Lee&#8217;s
+        forecast is based on the emergence of a new cycle in the stock market, where
+        annual returns are expected to compound at a high rate. This cycle is being
+        driven by the younger generations, particularly millennials and Gen Z.</p>\\n\\n\\n\\n<p>&#8220;This
+        will be the 3rd time that stocks entered a cycle where annual returns compound
+        at high teens,&#8221; Lee said in an interview with CNBC&#8217;s Last Call.
+        </p>\\n\\n\\n\\n<figure class=\\\"wp-block-embed is-type-rich is-provider-twitter
+        wp-block-embed-twitter\\\"><div class=\\\"wp-block-embed__wrapper\\\">\\n<blockquote
+        class=\\\"twitter-tweet\\\" data-width=\\\"500\\\" data-dnt=\\\"true\\\"><p
+        lang=\\\"en\\\" dir=\\\"ltr\\\">.<a href=\\\"https://twitter.com/fundstrat?ref_src=twsrc%5Etfw\\\">@fundstrat</a>&#39;s
+        Tom Lee says the S&amp;P 500 will hit 15,000 by 2030. &quot;This will be the
+        3rd time that stocks entered a cycle where annual returns compound at high
+        teens.&quot;  <a href=\\\"https://twitter.com/search?q=%24SPX&amp;src=ctag&amp;ref_src=twsrc%5Etfw\\\">$SPX</a>
+        <a href=\\\"https://t.co/31vzaEaGpo\\\">pic.twitter.com/31vzaEaGpo</a></p>&mdash;
+        Last Call (@LastCallCNBC) <a href=\\\"https://twitter.com/LastCallCNBC/status/1806110011669549190?ref_src=twsrc%5Etfw\\\">June
+        26, 2024</a></blockquote><script async src=\\\"https://platform.twitter.com/widgets.js\\\"
+        charset=\\\"utf-8\\\"></script>\\n</div></figure>\\n\\n\\n\\n<p>The growth
+        of companies focused on artificial intelligence is expected to yield high
+        returns, according to Lee. Additionally, the increasing number of digital
+        laborers investing in the economy is contributing to this cycle.</p>\\n\\n\\n\\n<p>S&amp;P
+        500 ETF options provide investors with <a href=\\\"https://www.benzinga.com/money/best-sp-500-etfs\\\">multiple
+        ways to invest</a> in America&#8217;s largest 500 companies. Interested investors
+        may check out the <strong>Schwab U.S. Large-Cap ETF</strong> (NYSE:<a class=\\\"ticker\\\"
+        href=\\\"https://www.benzinga.com/stock/SCHX#NYSE\\\">SCHX</a>), <strong>Vanguard
+        S&amp;P 500 ETF</strong> (NYSE:<a class=\\\"ticker\\\" href=\\\"https://www.benzinga.com/stock/VOO#NYSE\\\">VOO</a>),
+        and<strong> iShares Core S&amp;P 500 ETF</strong> (NYSE:<a class=\\\"ticker\\\"
+        href=\\\"https://www.benzinga.com/stock/IVV#NYSE\\\">IVV</a>) to diversify
+        their portfolios.</p>\\n\\n\\n\\n<p><em>See Also: <a href=\\\"https://www.benzinga.com/news/24/06/39493328/hillary-clinton-offers-advice-to-biden-ahead-of-presidential-debate-its-a-waste-of-time-to-try-to-re?itm_source=parsely-api\\\"
+        target=\\\"_blank\\\" rel=\\\"noreferrer noopener\\\">Hillary Clinton Offers
+        Advice To Biden Ahead Of Presidential Debate: &#8216;It&#8217;s A Waste Of
+        Time To Try To Refute Mr. Trump&#8217;s Arguments&#8217;</a></em></p>\\n\\n\\n\\n<p><strong>Why
+        It Matters</strong>: Lee&#8217;s prediction is in stark contrast to the forecasts
+        of other financial experts. In May, <strong>Goldman Sachs</strong> predicted
+        a <a href=\\\"https://www.benzinga.com/markets/equities/24/05/38863242/stock-market-rally-for-2024-has-peaked-goldman-sachs-forecasts-flat-return-from-now-till-the-end\\\">flat
+        return for the S&amp;P 500</a> for the remainder of 2024, suggesting that
+        the stock market rally had peaked. However, Lee&#8217;s forecast indicates
+        a more extended period of growth.</p>\\n\\n\\n\\n<p>Another analyst, <strong>Gene
+        Munster</strong>, predicted that the stock market would continue to rise for
+        <a href=\\\"https://www.benzinga.com/markets/equities/24/05/38910879/stock-market-to-rally-for-3-5-years-before-ai-bubble-bursts-predicts-veteran-analyst-gene-munste\\\">another
+        three to five years</a> before an AI bubble bursts. This aligns with Lee&#8217;s
+        forecast of a sustained period of growth driven by AI-focused companies.</p>\\n\\n\\n\\n<p>However,
+        not all experts share this optimistic outlook. Economist <strong>Harry Dent</strong>
+        warned of a <a href=\\\"https://www.benzinga.com/analyst-ratings/analyst-color/24/06/39257592/economist-warns-crash-of-a-lifetime-is-coming-predicts-s-p-500-to-plummet-86-from-t\\\">looming
+        &#8220;crash of a lifetime&#8221;</a> due to the current &#8220;everything&#8221;
+        bubble, which he believes has yet to burst. Despite this, Lee&#8217;s prediction
+        suggests a period of sustained growth, particularly in the AI sector.</p>\\n\\n\\n\\n<p><em>Read
+        Next: <a href=\\\"https://www.benzinga.com/news/24/06/39516013/mark-cuban-accuses-trump-of-ripping-off-thousands-of-hard-working-americans-and-not-wanting-to-leave?itm_source=parsely-api\\\"
+        target=\\\"_blank\\\" rel=\\\"noreferrer noopener\\\">Mark Cuban Accuses Trump
+        Of Ripping Off &#8216;Thousands Of Hard Working Americans&#8217; And Not Wanting
+        To Leave The White House</a></em></p>\\n\\n\\n\\n<p>Image Via Shutterstock
+        </p>\\n\\n\\n\\n<p>This story was generated using <a href=\\\"https://www.benzinga.com/author/benzinga-neuro\\\">Benzinga
+        Neuro</a> and edited by <u><a href=\\\"https://www.benzinga.com/topic/Kaustubh-Bagalkote\\\"
+        target=\\\"_blank\\\" rel=\\\"noreferrer noopener\\\">Kaustubh Bagalkote</a></u></p>\",\"url\":\"https://www.benzinga.com/markets/equities/24/06/39519696/fundstrats-tom-lee-predicts-s-p-500-will-hit-15-000-by-2030-driven-by-gen-z-and-ai-wave\",\"image\":[{\"size\":\"large\",\"url\":\"https://cdn.benzinga.com/files/imagecache/2048x1536xUP/images/story/2024/06/27/Southwest-Gas-Holdings-Inc-.jpeg\"},{\"size\":\"thumb\",\"url\":\"https://cdn.benzinga.com/files/imagecache/250x187xUP/images/story/2024/06/27/Southwest-Gas-Holdings-Inc-.jpeg\"},{\"size\":\"small\",\"url\":\"https://cdn.benzinga.com/files/imagecache/1024x768xUP/images/story/2024/06/27/Southwest-Gas-Holdings-Inc-.jpeg\"}],\"channels\":[{\"name\":\"Equities\"},{\"name\":\"News\"},{\"name\":\"Guidance\"},{\"name\":\"Economics\"},{\"name\":\"Markets\"},{\"name\":\"Analyst
+        Ratings\"}],\"stocks\":[{\"name\":\"IVV\"},{\"name\":\"SCHX\"},{\"name\":\"VOO\"}],\"tags\":[{\"name\":\"Fundstrat
+        Global Advisors\"},{\"name\":\"Kaustubh Bagalkote\"},{\"name\":\"Tom Lee\"}]},{\"id\":39519681,\"author\":\"Benzinga
+        Newsdesk\",\"created\":\"Thu, 27 Jun 2024 06:08:36 -0400\",\"updated\":\"Thu,
+        27 Jun 2024 06:08:37 -0400\",\"title\":\"Assure Holdings  On Wednesday Filed
+        Two Form RWs, Requesting Withdrawal Of Offering And Business Combination Filings\",\"teaser\":\"\",\"body\":\"\",\"url\":\"https://www.benzinga.com/m-a/24/06/39519681/assure-holdings-on-wednesday-filed-two-form-rws-requesting-withdrawal-of-offering-and-business-combi\",\"image\":[],\"channels\":[{\"name\":\"M&A\"},{\"name\":\"News\"},{\"name\":\"Offerings\"}],\"stocks\":[{\"name\":\"IONM\"}],\"tags\":[]},{\"id\":39519678,\"author\":\"Benzinga
+        Newsdesk\",\"created\":\"Thu, 27 Jun 2024 06:07:25 -0400\",\"updated\":\"Thu,
+        27 Jun 2024 06:07:25 -0400\",\"title\":\"LanzaTech and LanzaJet Introduce
+        CirculAir for Sustainable Aviation Fuel\",\"teaser\":\"LanzaTech Global, Inc.\_(NASDAQ:LNZA),
+        the carbon recycling company transforming waste carbon into sustainable fuels,
+        chemicals, and materials, and\_LanzaJet, Inc., a leading sustainable fuels
+        technology company\",\"body\":\"<p><a href=\\\"https://www.globenewswire.com/Tracker?data=hzva6c58Hgdr-3ljzxFh_1jkzXsUHnGwpJbfp6TLLSEmnrWYDKw2rZCvnI1CtH1f5Mx1-EZsjnrJjJdNSuPA69Q9niQny5l2i_yGWp5vkZQ=\\\"
+        target=\\\"_blank\\\">LanzaTech Global, Inc.</a>&nbsp;(NASDAQ:<a class=\\\"ticker\\\"
+        href=\\\"https://www.benzinga.com/stock/LNZA#NASDAQ\\\">LNZA</a>), the carbon
+        recycling company transforming waste carbon into sustainable fuels, chemicals,
+        and materials, and&nbsp;<a href=\\\"https://www.globenewswire.com/Tracker?data=hzva6c58Hgdr-3ljzxFh_07GxgCzPvFFKv5K8IRKKsqDthIMnkO744UmX8P-jxV_ABEPwTAZKNl_1zU9b0Asvg==\\\"
+        target=\\\"_blank\\\">LanzaJet, Inc.</a>, a leading sustainable fuels technology
+        company and fuels producer, are launching CirculAir&trade;, a new joint offering
+        to convert waste, carbon, and renewable power into sustainable aviation fuel
+        (SAF) and immediately accelerate decarbonization of the aviation industry
+        globally. CirculAir is a breakthrough offering that provides an economical
+        and commercialized alternative to Fischer-Tropsch technology to create eFuels,
+        Power-to-Liquids (PtL), and Waste-to-Fuels leveraging the already ASTM-approved
+        SAF production pathway that uses ethanol as the biointermediate and Alcohol-to-Jet
+        (ATJ) technology to produce SAF and Renewable Diesel (RD).<br />\\n&nbsp;</p>\\n\\n<p>CirculAir
+        is a formalized joint offering and end-to-end technology solution that turns
+        nearly any waste source including municipal solid waste (MSW), agricultural
+        residues, carbon emissions from industrial and refining processes, carbon
+        dioxide (CO2) through direct air capture, and renewable power into SAF. CirculAir
+        combines the groundbreaking technologies of LanzaTech and LanzaJet to form
+        an efficient and economically compelling offering that provides the aviation
+        industry with a solution to produce waste-based SAF on a global scale. CirculAir
+        will combine LanzaTech and LanzaJet&#39;s technologies; first incorporating
+        LanzaTech&#39;s novel gas fermentation technology to convert nearly any waste
+        resource into CarbonSmart&trade; ethanol and then second, executing LanzaJet&#39;s
+        Alcohol-to-Jet (ATJ) technology by taking the ethanol and converting it to
+        drop-in SAF. The SAF made through this process is expected to reduce aviation
+        emissions by at least&nbsp;85%&nbsp;and can also produce carbon negative results,
+        depending on the feedstock.</p>\\n\\n<p>SAF is estimated to account for 65&ndash;70%&nbsp;of
+        overall aviation emissions reduction to achieve net zero by 2050, making it
+        a critical tool for this hard-to-abate industry; however, historic supply
+        constraints, high costs, and technical barriers have made it difficult for
+        the industry to default to SAF as the primary fuel source. CirculAir breaks
+        down these barriers. The technology is able to turn a wide range of waste-based
+        feedstocks into SAF, and it is being adopted by a range of customers across
+        the globe. This widespread adoption is projected to accelerate the production
+        and economies of scale necessary to bring down the global cost of SAF.</p>\",\"url\":\"https://www.benzinga.com/news/24/06/39519678/lanzatech-and-lanzajet-introduce-circulair-for-sustainable-aviation-fuel\",\"image\":[],\"channels\":[{\"name\":\"News\"}],\"stocks\":[{\"name\":\"LNZA\"}],\"tags\":[]},{\"id\":39519665,\"author\":\"Benzinga
+        Newsdesk\",\"created\":\"Thu, 27 Jun 2024 06:06:55 -0400\",\"updated\":\"Thu,
+        27 Jun 2024 06:06:56 -0400\",\"title\":\"Needham Reiterates Buy on Sarepta
+        Therapeutics, Maintains $235 Price Target\",\"teaser\":\"Needham  analyst
+        Gil Blum   reiterates Sarepta Therapeutics (NASDAQ:SRPT) with a Buy and maintains
+        $235 price target.\",\"body\":\"Needham  analyst Gil Blum   reiterates Sarepta
+        Therapeutics (NASDAQ:<a class=\\\"ticker\\\" href=\\\"https://www.benzinga.com/stock/SRPT#NASDAQ\\\">SRPT</a>)
+        with a Buy and maintains $235 price target.\",\"url\":\"https://www.benzinga.com/news/24/06/39519665/needham-reiterates-buy-on-sarepta-therapeutics-maintains-235-price-target\",\"image\":[],\"channels\":[{\"name\":\"News\"},{\"name\":\"Price
+        Target\"},{\"name\":\"Reiteration\"},{\"name\":\"Analyst Ratings\"}],\"stocks\":[{\"name\":\"SRPT\"}],\"tags\":[]},{\"id\":39519662,\"author\":\"Benzinga
+        Newsdesk\",\"created\":\"Thu, 27 Jun 2024 06:05:52 -0400\",\"updated\":\"Thu,
+        27 Jun 2024 06:05:53 -0400\",\"title\":\"GNL Reduces Debt with $170M Sale
+        of Americold-Leased Properties\",\"teaser\":\"Global Net Lease, Inc. (NYSE:GNL)
+        (&#34;GNL&#34; or the &#34;Company&#34;) today announced the successful disposition
+        of a portfolio of nine cold storage properties that are currently leased to
+        subsidiaries of\",\"body\":\"<p>Global Net Lease, Inc. (NYSE:<a class=\\\"ticker\\\"
+        href=\\\"https://www.benzinga.com/stock/GNL#NYSE\\\">GNL</a>) (&quot;GNL&quot;
+        or the &quot;Company&quot;) today announced the successful disposition of
+        a portfolio of nine cold storage properties that are currently leased to subsidiaries
+        of Americold Realty Trust, Inc. (NYSE:<a class=\\\"ticker\\\" href=\\\"https://www.benzinga.com/stock/COLD#NYSE\\\">COLD</a>)
+        for&nbsp;$170 million, at a&nbsp;7.88%&nbsp;cash cap rate on 3.3 years of
+        weighted average remaining lease-term.</p>\\n\\n<p>This disposition is a significant
+        achievement in GNL&#39;s ongoing strategic disposition initiative and aligns
+        with the Company&#39;s 2024 full-year&nbsp;guidance, which projected a disposition
+        cash cap rate range of&nbsp;7%&nbsp;to&nbsp;8%. GNL plans to use the net proceeds
+        from this sale to reduce outstanding debt and further lower the Company&#39;s
+        leverage. The sale of this portfolio, which GNL acquired for&nbsp;$153.4 million,
+        is part of the previously announced&nbsp;$567 million1&nbsp;of closed and
+        pipeline dispositions at a cash cap rate of&nbsp;7.2%.</p>\",\"url\":\"https://www.benzinga.com/news/24/06/39519662/gnl-reduces-debt-with-170m-sale-of-americold-leased-properties\",\"image\":[],\"channels\":[{\"name\":\"News\"},{\"name\":\"Asset
+        Sales\"}],\"stocks\":[{\"name\":\"COLD\"},{\"name\":\"GNL\"}],\"tags\":[]},{\"id\":39519629,\"author\":\"Benzinga
+        Newsdesk\",\"created\":\"Thu, 27 Jun 2024 06:04:50 -0400\",\"updated\":\"Thu,
+        27 Jun 2024 06:04:51 -0400\",\"title\":\"Nkarta Begins Ntrust-1 Clinical Trial
+        Of NKX019 In Lupus Nephritis, With The First Patient In Screening; Says IND
+        Cleared For Ntrust-2\",\"teaser\":\"The company also announced the clearance
+        by the U.S. Food and Drug Administration (FDA) of its second Investigational
+        New Drug (IND) application for NKX019 in autoimmune disease.\\n\\nWith this
+        new IND, Nkarta plans to\",\"body\":\"<p>The company also announced the clearance
+        by the U.S. Food and Drug Administration (FDA) of its second Investigational
+        New Drug (IND) application for NKX019 in autoimmune disease.</p>\\n\\n<p>With
+        this new IND, Nkarta plans to initiate Ntrust-2, an open-label, multi-center
+        clinical trial of NKX019 for the treatment of systemic sclerosis (SSc, scleroderma),
+        idiopathic inflammatory myopathy (IIM, myositis) and ANCA-associated vasculitis
+        (AAV).</p>\\n\\n<p>Clinical data from Ntrust-1 and Ntrust-2 planned for 2025.</p>\",\"url\":\"https://www.benzinga.com/news/24/06/39519629/nkarta-begins-ntrust-1-clinical-trial-of-nkx019-in-lupus-nephritis-with-the-first-patient-in-screeni\",\"image\":[],\"channels\":[{\"name\":\"News\"}],\"stocks\":[{\"name\":\"NKTX\"}],\"tags\":[]},{\"id\":39519626,\"author\":\"Benzinga
+        Newsdesk\",\"created\":\"Thu, 27 Jun 2024 06:04:18 -0400\",\"updated\":\"Thu,
+        27 Jun 2024 06:04:19 -0400\",\"title\":\"Entero Therapeutics Publishes Innovative
+        Celiac Disease Research in Top Gastroenterology Journal\",\"teaser\":\"Entero
+        Therapeutics, Inc., (NASDAQ:ENTO), (&#34;Entero Therapeutics&#34; or the &#34;Company&#34;),
+        a clinical-stage biopharmaceutical company specializing in the development
+        of targeted, non-systemic therapies\",\"body\":\"<p>Entero Therapeutics, Inc.,
+        (NASDAQ:<a class=\\\"ticker\\\" href=\\\"https://www.benzinga.com/stock/ENTO#NASDAQ\\\">ENTO</a>),
+        (&quot;Entero Therapeutics&quot; or the &quot;Company&quot;), a clinical-stage
+        biopharmaceutical company specializing in the development of targeted, non-systemic
+        therapies for&nbsp;gastrointestinal (GI) diseases, today announced the publication
+        of &quot;<a href=\\\"https://www.globenewswire.com/Tracker?data=h1ge28PUKiAz2IQRtYAA0SJfZUgHAckbiDzteTYi9l8E2W0CnDTx_7ezI5x8VIMa_Wg2k3zipLcko2Av_SJvn_YqB86D2_mvrekcSAqxiQ6X9xBpjdri1PzvYFtLCS5UyIAfampZnL10YfhDRNPNN_QRw5fCtj5xjAdou5NqsB0k9gt5BdDl8iwvU7rc-8SH18hztI6ucqenOv4l7Y52Po1PwNhmZshxk4x1WTRu1EZPz5H5PVvedeWlwxDhfzf2EotxEigcF8uAmCKc-SX9nQ==\\\"
+        target=\\\"_blank\\\">A Composite Morphometric Duodenal Biopsy Mucosal Scale
+        for Celiac Disease Encompassing Both Morphology and Inflammation</a>&quot;
+        in&nbsp;<em>Clinical Gastroenterology and Hepatology</em>, a pre-eminent journal
+        of the American Gastroenterological Association (AGA) that publishes innovative
+        diagnostic and therapeutic advances in clinical gastroenterology<em>.</em></p>\\n\\n<p>As
+        the number of promising therapies for celiac disease (CeD) grows, so does
+        the need to improve the measurement of clinically relevant histological endpoints.
+        The new approach presented in a peer-reviewed publication, led by Jack Syage,
+        Ph.D., President and Chief Scientific Officer of Entero Therapeutics, recognized
+        the need to advance beyond qualitative measures of histologic small intestinal
+        health and to develop a more accurate and sensitive scale based on the independent
+        quantitative measures of architectural changes (villus height to crypt depth
+        ratio, Vh:Cd) and inflammation (intraepithelial lymphocyte count, IEL) already
+        in use. The team created a composite score (VCIEL) for these two measures
+        that helps overcome the individual variances to improve the overall accuracy
+        of histological evaluation. The publication demonstrated the significant benefits
+        of the VCIEL scale based on the results of four previous clinical trials.
+        The significance of this achievement was highlighted in a special editorial
+        feature by the journal, demonstrating the importance of this novel metric
+        to CeD researchers.</p>\",\"url\":\"https://www.benzinga.com/news/24/06/39519626/entero-therapeutics-publishes-innovative-celiac-disease-research-in-top-gastroenterology-journal\",\"image\":[],\"channels\":[{\"name\":\"News\"}],\"stocks\":[{\"name\":\"ENTO\"}],\"tags\":[]},{\"id\":39519625,\"author\":\"Benzinga
+        Newsdesk\",\"created\":\"Thu, 27 Jun 2024 06:04:17 -0400\",\"updated\":\"Thu,
+        27 Jun 2024 06:04:17 -0400\",\"title\":\"Nkarta Initiates Ntrust-1 Of NKX019
+        In Lupus Nephritis, With First Patient In Screening. FDA Also Clears Second
+        Investigational New Drug Application For NKX019 In Autoimmune Disease\",\"teaser\":\"\",\"body\":\"\",\"url\":\"https://www.benzinga.com/general/biotech/24/06/39519625/nkarta-initiates-ntrust-1-of-nkx019-in-lupus-nephritis-with-first-patient-in-screening-fda-also-c\",\"image\":[],\"channels\":[{\"name\":\"Biotech\"},{\"name\":\"News\"},{\"name\":\"Health
+        Care\"},{\"name\":\"General\"}],\"stocks\":[{\"name\":\"NKTX\"}],\"tags\":[]},{\"id\":39519611,\"author\":\"Benzinga
+        Neuro\",\"created\":\"Thu, 27 Jun 2024 06:03:50 -0400\",\"updated\":\"Thu,
+        27 Jun 2024 06:06:56 -0400\",\"title\":\"International Paper Shares Dip 15%
+        In Pre-Market After Suzano Drops Acquisition Pursuit\",\"teaser\":\" \",\"body\":\"<p><strong>Suzano
+        SA</strong> (NYSE:<a class=\\\"ticker\\\" href=\\\"https://www.benzinga.com/stock/SUZ#NYSE\\\">SUZ</a>)
+        has decided to abandon its pursuit to acquire <strong>International Paper
+        Co.</strong> (NYSE:<a class=\\\"ticker\\\" href=\\\"https://www.benzinga.com/stock/IP#NYSE\\\">IP</a>),&nbsp;one
+        of&nbsp;North America&#8217;s&nbsp;largest recyclers and a global producer
+        of packaging, pulp and other fiber-based products. This news triggered a nearly
+        15% drop in International Paper&#8217;s shares during pre-market trading on
+        Thursday.</p>\\n\\n\\n\\n<p>Suzano&#8217;s decision was prompted by International
+        Paper&#8217;s rejection of its advances, Bloomberg <a href=\\\"https://www.bloomberg.com/news/articles/2024-06-26/suzano-drops-its-pursuit-of-international-paper-acquisition\\\">reported</a>
+        on Thursday. Instead, International Paper has chosen to focus on its own merger
+        plans with a different competitor.</p>\\n\\n\\n\\n<p>At the time of writing,
+        International Paper&#8217;s shares were trading at $39.67, a significant drop
+        from Wednesday&#8217;s close of $46.61, according to <a href=\\\"https://pro.benzinga.com\\\">Benzinga
+        Pro</a>.</p>\\n\\n\\n\\n<p><em>See Also: <a href=\\\"https://www.benzinga.com/markets/cryptocurrency/24/06/39448955/dogecoin-killer-shiba-inu-falters-here-is-what-these-key-indicators-reveal-about-its-short?itm_source=parsely-api\\\"
+        target=\\\"_blank\\\" rel=\\\"noreferrer noopener\\\">&#8216;Dogecoin Killer&#8217;
+        Shiba Inu Falters \u2014 Here Is What These Key Indicators Reveal About Its
+        Short-Term Prosp</a></em></p>\\n\\n\\n\\n<p>Suzano, a Brazil-based company,
+        had initially proposed a $15 billion acquisition offer to International Paper.
+        However, the deal was based on the condition that International Paper abandon
+        its plans to acquire British packaging firm <strong>DS Smith.</strong></p>\\n\\n\\n\\n<p>Suzano
+        stated that it was unable to engage International Paper in serious discussions
+        and was not willing to increase its offer. This announcement led Suzano&#8217;s
+        U.S.-listed shares to see an 11.94% jump in the pre-market on Thursday.</p>\\n\\n\\n\\n<p>Suzano
+        had hoped to negotiate on &#8220;private, confidential and amicable terms,&#8221;
+        as per its statement. However, as this was not feasible, the company decided
+        to terminate the talks.</p>\\n\\n\\n\\n<p>This development simplifies International
+        Paper&#8217;s plan to acquire DS Smith Plc, a deal that is expected to close
+        in the fourth quarter. If Suzano&#8217;s acquisition had been successful,
+        the world&#8217;s largest pulp producer would have had the chance to expand
+        internationally and diversify into the more stable packaging sector. However,
+        there were investor concerns about Suzano&#8217;s ability to maintain its
+        investment grade if it took on additional debt for the deal.</p>\\n\\n\\n\\n<p><em>Read
+        Next: <a href=\\\"https://www.benzinga.com/markets/equities/24/06/39493523/rivian-lucid-micron-technology-novo-nordisk-tesla-why-these-5-stocks-are-on-investors-radars-tod?itm_source=parsely-api\\\"
+        target=\\\"_blank\\\" rel=\\\"noreferrer noopener\\\">RIVN, LCID, MU, NVO,
+        TSLA: Top 5 Trending Stocks Today</a></em></p>\\n\\n\\n\\n<p><em>Image via
+        Shutterstock</em></p>\\n\\n\\n\\n<p>This story was generated using <a href=\\\"https://www.benzinga.com/author/benzinga-neuro\\\">Benzinga
+        Neuro</a> and edited by <u><a href=\\\"https://www.benzinga.com/topic/Pooja-Rajkumari\\\"
+        target=\\\"_blank\\\" rel=\\\"noreferrer noopener\\\">Pooja Rajkumari</a></u></p>\",\"url\":\"https://www.benzinga.com/markets/equities/24/06/39519611/international-paper-shares-dip-15-in-pre-market-after-suzano-drops-acquisition-pursuit\",\"image\":[{\"size\":\"thumb\",\"url\":\"https://cdn.benzinga.com/files/imagecache/250x187xUP/images/story/2024/06/27/Down-Crisis-Financial-Business-Market-Gr.jpeg\"},{\"size\":\"small\",\"url\":\"https://cdn.benzinga.com/files/imagecache/1024x768xUP/images/story/2024/06/27/Down-Crisis-Financial-Business-Market-Gr.jpeg\"},{\"size\":\"large\",\"url\":\"https://cdn.benzinga.com/files/imagecache/2048x1536xUP/images/story/2024/06/27/Down-Crisis-Financial-Business-Market-Gr.jpeg\"}],\"channels\":[{\"name\":\"Equities\"},{\"name\":\"M&A\"},{\"name\":\"News\"},{\"name\":\"Pre-Market
+        Outlook\"},{\"name\":\"Markets\"},{\"name\":\"General\"}],\"stocks\":[{\"name\":\"IP\"},{\"name\":\"SUZ\"}],\"tags\":[{\"name\":\"Pooja
+        Rajkumari\"},{\"name\":\"Stories That Matter\"}]},{\"id\":39519608,\"author\":\"Benzinga
+        Newsdesk\",\"created\":\"Thu, 27 Jun 2024 06:02:54 -0400\",\"updated\":\"Thu,
+        27 Jun 2024 06:02:54 -0400\",\"title\":\"Wolfe Research Downgrades Agilent
+        Technologies to Peer Perform\",\"teaser\":\"Wolfe Research  analyst Doug Schenkel
+        \  downgrades Agilent Technologies (NYSE:A) from Outperform to Peer Perform.\",\"body\":\"Wolfe
+        Research  analyst Doug Schenkel   downgrades Agilent Technologies (NYSE:<a
+        class=\\\"ticker\\\" href=\\\"https://www.benzinga.com/stock/A#NYSE\\\">A</a>)
+        from Outperform to Peer Perform.\",\"url\":\"https://www.benzinga.com/news/24/06/39519608/wolfe-research-downgrades-agilent-technologies-to-peer-perform\",\"image\":[],\"channels\":[{\"name\":\"News\"},{\"name\":\"Downgrades\"},{\"name\":\"Analyst
+        Ratings\"}],\"stocks\":[{\"name\":\"A\"}],\"tags\":[]},{\"id\":39519607,\"author\":\"Benzinga
+        Newsdesk\",\"created\":\"Thu, 27 Jun 2024 06:02:45 -0400\",\"updated\":\"Thu,
+        27 Jun 2024 06:02:45 -0400\",\"title\":\"Acuity Brands Q3 2024 Adj EPS $4.15
+        Beats $4.13 Estimate\",\"teaser\":\"\",\"body\":\"\",\"url\":\"https://www.benzinga.com/news/earnings/24/06/39519607/acuity-brands-q3-2024-adj-eps-4-15-beats-4-13-estimate\",\"image\":[],\"channels\":[{\"name\":\"Earnings\"},{\"name\":\"Earnings
+        Beats\"},{\"name\":\"Earnings Misses\"},{\"name\":\"News\"}],\"stocks\":[{\"name\":\"AYI\"}],\"tags\":[]},{\"id\":39519592,\"author\":\"Benzinga
+        Newsdesk\",\"created\":\"Thu, 27 Jun 2024 06:02:29 -0400\",\"updated\":\"Thu,
+        27 Jun 2024 06:02:30 -0400\",\"title\":\"RH Chairman & CEO Gary Friedman Buys
+        $10M Of RH Stock At Average Price Per Share Of $216.10 Representing 46,274
+        Shares\",\"teaser\":\"With this purchase, Friedman beneficially owns as of
+        June 26, 2024, 5.05 million shares, or\_25.1%\_of the outstanding shares of
+        RH common stock, based on 18.44 million shares outstanding as of June 7, 2024,
+        as\",\"body\":\"<p>With this purchase, Friedman beneficially owns as of June
+        26, 2024, 5.05 million shares, or&nbsp;25.1%&nbsp;of the outstanding shares
+        of RH common stock, based on 18.44 million shares outstanding as of June 7,
+        2024, as reported in RH&#39;s&nbsp;first quarter&nbsp;fiscal 2024 Form 10-Q.
+        This represents an increase in Friedman&#39;s beneficial ownership by&nbsp;0.2%.&nbsp;</p>\",\"url\":\"https://www.benzinga.com/news/24/06/39519592/rh-chairman-ceo-gary-friedman-buys-10m-of-rh-stock-at-average-price-per-share-of-216-10-representing\",\"image\":[],\"channels\":[{\"name\":\"News\"}],\"stocks\":[{\"name\":\"RH\"}],\"tags\":[]},{\"id\":39519584,\"author\":\"Benzinga
+        Newsdesk\",\"created\":\"Thu, 27 Jun 2024 06:01:53 -0400\",\"updated\":\"Thu,
+        27 Jun 2024 06:01:53 -0400\",\"title\":\"Acuity Brands Q3 2024 GAAP EPS $3.62
+        Misses $3.68 Estimate, Sales $968.100M Miss $1.009B Estimate\",\"teaser\":\"\",\"body\":\"\",\"url\":\"https://www.benzinga.com/news/earnings/24/06/39519584/acuity-brands-q3-2024-gaap-eps-3-62-misses-3-68-estimate-sales-968-100m-miss-1-009b-estimate\",\"image\":[],\"channels\":[{\"name\":\"Earnings\"},{\"name\":\"Earnings
+        Misses\"},{\"name\":\"News\"}],\"stocks\":[{\"name\":\"AYI\"}],\"tags\":[]},{\"id\":39519493,\"author\":\"Benzinga
+        Neuro\",\"created\":\"Thu, 27 Jun 2024 05:58:54 -0400\",\"updated\":\"Thu,
+        27 Jun 2024 05:58:55 -0400\",\"title\":\"Morgan Stanley To Roll Out OpenAI-Powered
+        Assistant For Financial Advisors: 'Quality And Depth Of The Notes Are Just
+        Significantly Better'\",\"teaser\":\"Morgan Stanley is set to launch an AI-powered
+        assistant that will revolutionize the workflow of its financial advisors.\",\"body\":\"<p><strong>Morgan
+        Stanley</strong> (NYSE:<a class=\\\"ticker\\\" href=\\\"https://www.benzinga.com/stock/MS#NYSE\\\">MS</a>)
+        is set to launch an AI-powered assistant to enhance the workflow of its financial
+        advisors.</p>\\n\\n\\n\\n<p><strong>What Happened</strong>: The AI assistant,
+        named <strong>Debrief</strong>, will automate the note-taking process during
+        client meetings, creating draft emails and summaries of the discussions, CNBC
+        <a href=\\\"https://www.cnbc.com/2024/06/26/morgan-stanley-openai-powered-assistant-for-wealth-advisors.html\\\">reported</a>
+        on Thursday. The program, built using <strong>Microsoft Corp.-backed OpenAI&#8217;s</strong>
+        GPT-4, will be rolled out to the firm&#8217;s approximately 15,000 advisors
+        by early July.</p>\\n\\n\\n\\n<p>\\\"What we're finding is that the quality
+        and depth of the notes are just significantly better,\\\" <strong>Jeff McMillan</strong>,
+        Morgan Stanley&#8217;s head of firmwide artificial intelligence said. \\\"The
+        truth is, this does a better job of taking notes than the average human.\\\"</p>\\n\\n\\n\\n<p>The
+        AI assistant will also free up valuable time for advisors, potentially leading
+        to increased client engagement and business growth.</p>\\n\\n\\n\\n<p>Debrief
+        will initially be used in client meetings, with future versions allowing advisors
+        to use the program on corporate devices during in-person meetings. Clients
+        must consent to be recorded each time Debrief is used.</p>\\n\\n\\n\\n<p>\\\"As
+        a financial adviser I'm doing four, five or six meetings a day,\\\" said <strong>Don
+        Whitehead</strong>, a Houston-based advisor who's been testing the software.
+        By \\\"having the note-taking service built in through AI, you can really
+        be invested in the meeting, you're actually a lot more present.\\\"</p>\\n\\n\\n\\n<p><em>See
+        Also: <a href=\\\"https://www.benzinga.com/news/24/06/39450621/mark-cuban-falls-victim-to-this-common-account-takeover-tactic-by-hackers-and-loses-access-to-his-gm?itm_source=parsely-api\\\"
+        target=\\\"_blank\\\" rel=\\\"noreferrer noopener\\\">Mark Cuban Falls Victim
+        To This Common Account Takeover Tactic By Hackers And Loses Access To His
+        Gmail: Here&#8217;s How You Can Avoid It</a></em></p>\\n\\n\\n\\n<p><strong>Why
+        It Matters</strong>: This move by Morgan Stanley is in line with the increasing
+        adoption of AI in the financial sector. Earlier in May, a PricewaterhouseCoopers
+        report <a href=\\\"https://www.benzinga.com/news/24/05/38931261/pwc-report-shows-ai-driven-sectors-surging-in-productivity-signaling-economic-upswing\\\">highlighted
+        a significant surge in productivity</a> in AI-driven sectors, including professional
+        and financial services. This growth was nearly five times faster than in other
+        sectors.</p>\\n\\n\\n\\n<p>Moreover, OpenAI&#8217;s ChatGPT Enterprise has
+        been gaining traction in the industry, with PwC becoming <a href=\\\"https://www.benzinga.com/news/24/05/39058054/big-four-accounting-firm-becomes-openais-largest-chatgpt-enterprise-customer\\\">its
+        largest customer</a> in May. A study by the University of Chicago also found
+        that OpenAI&#8217;s GPT-4 had a relative advantage over humans in <a href=\\\"https://www.benzinga.com/news/24/05/39055523/openais-chatgpt-4-has-a-relative-advantage-over-humans-in-financial-analysis-study-finds-even-withou\\\">financial
+        analysis and forecasting</a>, further underlining the potential of AI in the
+        financial sector.</p>\\n\\n\\n\\n<p>This development comes at a time when
+        the financial services industry is increasingly relying on AI and machine
+        learning technologies to <a href=\\\"https://www.benzinga.com/partner/general/24/04/38278223/the-future-of-finance-how-ai-and-machine-learning-are-transforming-financial-call-center-operatio\\\">enhance
+        customer experiences and operational efficiency</a>. The integration of AI
+        in financial services is seen as crucial for adapting to remote working conditions
+        and meeting evolving consumer needs.</p>\\n\\n\\n\\n<p><em>Read Next: <a href=\\\"https://www.benzinga.com/general/education/24/06/39466991/michael-saylor-2012-apple-stock-prediction-goes-viral-heres-what-bitcoin-bull-got-right-whoever?itm_source=parsely-api\\\"
+        target=\\\"_blank\\\" rel=\\\"noreferrer noopener\\\">Michael Saylor 2012
+        Apple Stock Prediction Goes Viral, Here's What Bitcoin Bull Got Right: \u2018Whoever
+        Is Selling That Stock Must Be A Moron&#8217;</a></em></p>\\n\\n\\n\\n<p>Image
+        Via Shutterstock </p>\\n\\n\\n\\n<p>This story was generated using <a href=\\\"https://www.benzinga.com/author/benzinga-neuro\\\">Benzinga
+        Neuro</a> and edited by <u><a href=\\\"https://www.benzinga.com/topic/Kaustubh-Bagalkote\\\"
+        target=\\\"_blank\\\" rel=\\\"noreferrer noopener\\\">Kaustubh Bagalkote</a></u></p>\",\"url\":\"https://www.benzinga.com/news/24/06/39519493/morgan-stanley-to-roll-out-openai-powered-assistant-for-financial-advisors-quality-and-depth-of-the\",\"image\":[{\"size\":\"thumb\",\"url\":\"https://cdn.benzinga.com/files/imagecache/250x187xUP/images/story/2024/06/27/morgan-stanley-shutter3.jpeg\"},{\"size\":\"small\",\"url\":\"https://cdn.benzinga.com/files/imagecache/1024x768xUP/images/story/2024/06/27/morgan-stanley-shutter3.jpeg\"},{\"size\":\"large\",\"url\":\"https://cdn.benzinga.com/files/imagecache/2048x1536xUP/images/story/2024/06/27/morgan-stanley-shutter3.jpeg\"}],\"channels\":[{\"name\":\"News\"},{\"name\":\"Global\"},{\"name\":\"Markets\"},{\"name\":\"Tech\"}],\"stocks\":[{\"name\":\"MS\"}],\"tags\":[{\"name\":\"artificial
+        intelligence\"},{\"name\":\"ChatGPT\"},{\"name\":\"Kaustubh Bagalkote\"},{\"name\":\"Morgan
+        Stanley\"},{\"name\":\"OpenAi\"}]},{\"id\":39519482,\"author\":\"Benzinga
+        Newsdesk\",\"created\":\"Thu, 27 Jun 2024 05:56:34 -0400\",\"updated\":\"Thu,
+        27 Jun 2024 05:56:35 -0400\",\"title\":\"Nokia Inks Deal With The French State
+        Regarding The Sale Of Submarine Networks Business ASN For An Enterprise Value
+        Of \u20AC350M\",\"teaser\":\"Nokia will retain a 20% shareholding with board
+        representation to ensure a smooth transition until targeted exit, at which
+        point the French State would acquire Nokia\u2019s remaining interest.\\n\\n\_\\n\\nThe
+        sale is\",\"body\":\"<div>Nokia will retain a 20% shareholding with board
+        representation to ensure a smooth transition until targeted exit, at which
+        point the French State would acquire Nokia&rsquo;s remaining interest.</div>\\n\\n<div>&nbsp;</div>\\n\\n<div>The
+        sale is expected to close at the end of 2024 or beginning of 2025, subject
+        to formal consultation of ASN&rsquo;s French Works Council and other customary
+        closing conditions and regulatory approvals.</div>\",\"url\":\"https://www.benzinga.com/news/24/06/39519482/nokia-inks-deal-with-the-french-state-regarding-the-sale-of-submarine-networks-business-asn-for-an-e\",\"image\":[],\"channels\":[{\"name\":\"News\"},{\"name\":\"Asset
+        Sales\"}],\"stocks\":[{\"name\":\"NOK\"}],\"tags\":[]},{\"id\":39519479,\"author\":\"Benzinga
+        Newsdesk\",\"created\":\"Thu, 27 Jun 2024 05:55:53 -0400\",\"updated\":\"Thu,
+        27 Jun 2024 05:55:54 -0400\",\"title\":\"Stifel Initiates Coverage On Jasper
+        Therapeutics with Buy Rating, Announces Price Target of $86\",\"teaser\":\"Stifel
+        \ analyst Ben Burnett   initiates coverage on Jasper Therapeutics (NASDAQ:JSPR)
+        with a Buy rating and announces Price Target of $86.\",\"body\":\"Stifel  analyst
+        Ben Burnett   initiates coverage on Jasper Therapeutics (NASDAQ:<a class=\\\"ticker\\\"
+        href=\\\"https://www.benzinga.com/stock/JSPR#NASDAQ\\\">JSPR</a>) with a Buy
+        rating and announces Price Target of $86.\",\"url\":\"https://www.benzinga.com/news/24/06/39519479/stifel-initiates-coverage-on-jasper-therapeutics-with-buy-rating-announces-price-target-of-86\",\"image\":[],\"channels\":[{\"name\":\"News\"},{\"name\":\"Price
+        Target\"},{\"name\":\"Initiation\"},{\"name\":\"Analyst Ratings\"}],\"stocks\":[{\"name\":\"JSPR\"}],\"tags\":[]},{\"id\":39519471,\"author\":\"Benzinga
+        Newsdesk\",\"created\":\"Thu, 27 Jun 2024 05:54:22 -0400\",\"updated\":\"Thu,
+        27 Jun 2024 05:54:22 -0400\",\"title\":\"Roth MKM Initiates Coverage On Denison
+        Mines with Buy Rating, Announces Price Target of $2.6\",\"teaser\":\"Roth
+        MKM  analyst Joe Reagor   initiates coverage on Denison Mines (AMEX:DNN) with
+        a Buy rating and announces Price Target of $2.6.\",\"body\":\"Roth MKM  analyst
+        Joe Reagor   initiates coverage on Denison Mines (AMEX:<a class=\\\"ticker\\\"
+        href=\\\"https://www.benzinga.com/stock/DNN#AMEX\\\">DNN</a>) with a Buy rating
+        and announces Price Target of $2.6.\",\"url\":\"https://www.benzinga.com/news/24/06/39519471/roth-mkm-initiates-coverage-on-denison-mines-with-buy-rating-announces-price-target-of-2-6\",\"image\":[],\"channels\":[{\"name\":\"News\"},{\"name\":\"Price
+        Target\"},{\"name\":\"Initiation\"},{\"name\":\"Analyst Ratings\"}],\"stocks\":[{\"name\":\"DNN\"}],\"tags\":[]},{\"id\":39519449,\"author\":\"Lekha
+        Gupta\",\"created\":\"Thu, 27 Jun 2024 05:52:52 -0400\",\"updated\":\"Thu,
+        27 Jun 2024 05:52:53 -0400\",\"title\":\"Is BP Bailing on Green? Reportedly
+        Shifts Gears From Renewables To Oil And Gas\",\"teaser\":\"BP reportedly shifts
+        focus back to oil and gas, halting new offshore wind projects and implementing
+        hiring freeze, due to investor dissatisfaction with energy transition strategy.\",\"body\":\"<p><strong>BP
+        p.l.c.</strong> (NYSE:<a class=\\\"ticker\\\" href=\\\"https://www.benzinga.com/stock/BP#NYSE\\\">BP</a>)
+        reportedly implemented a hiring freeze and halted new offshore wind projects,
+        shifting focus back to oil and gas due to investor dissatisfaction with the
+        company&#8217;s energy transition strategy.</p>\\n\\n\\n\\n<p>These moves
+        are part of CEO Murray Auchincloss&#8217; strategy to reduce investments in
+        high-budget, low-carbon projects, especially offshore wind, which are not
+        expected to generate immediate cash flow, reported Reuters.</p>\\n\\n\\n\\n<p>These
+        actions signify a major departure from the approach of Auchincloss&#8217;
+        predecessor, Bernard Looney, who aimed to <a target=\\\"_blank\\\" href=\\\"https://www.benzinga.com/markets/equities/23/09/34526407/oil-giant-bps-ceo-resigns-amid-investigation-on-personal-conduct\\\"
+        rel=\\\"noreferrer noopener\\\">transition away from fossil fuels quickly</a>.</p>\\n\\n\\n\\n<p>The
+        shift has affected BP&#8217;s stock performance, as returns from renewable
+        energy projects have declined, while profits from oil and gas have soared
+        in the aftermath of the COVID-19 pandemic and Russia&#8217;s invasion of Ukraine.</p>\\n\\n\\n\\n<p>Auchincloss
+        and Chief Financial Officer Kate Thomson have prioritized investing in and
+        acquiring new oil and gas assets, with a particular focus on the Gulf of Mexico
+        and U.S. onshore shale basins, where BP already has significant operations,
+        the report added, citing people familiar with the matter.</p>\\n\\n\\n\\n<p><strong><em>Related</em></strong><em>:
+        <a target=\\\"_blank\\\" href=\\\"https://www.benzinga.com/markets/equities/24/06/39247864/bp-tightens-workplace-relationship-rules-after-ceo-firing-report\\\"
+        rel=\\\"noreferrer noopener\\\">BP Tightens Workplace Relationship Rules After
+        CEO Firing: Report</a></em></p>\\n\\n\\n\\n<p>BP said in a statement to Reuters
+        that Auchincloss introduced six priorities &#8220;to deliver as a simpler,
+        more focused and higher value company.&#8221;</p>\\n\\n\\n\\n<p>&#8220;The
+        actions we are taking are part of delivering this &#8211; and of course are
+        all in service of our aim of growing the value of BP.&#8221;</p>\\n\\n\\n\\n<p>As
+        per the report, BP has reassigned dozens of employees, who were previously
+        focused on identifying new renewable opportunities, to existing projects such
+        as offshore wind initiatives in Britain and Germany.</p>\\n\\n\\n\\n<p><strong><em>Read</em></strong><em>:
+        <a target=\\\"_blank\\\" href=\\\"https://www.benzinga.com/markets/equities/24/06/39416447/bp-doubles-down-on-biofuels-buys-out-bunge-bioenergia-for-1-4b\\\"
+        rel=\\\"noreferrer noopener\\\">BP Doubles Down On Biofuels: Buys Out Bunge
+        Bioenergia for $1.4B</a></em></p>\\n\\n\\n\\n<p>This week, BP said it plans
+        to expand and diversify its biofuel operations in Brazil after acquiring <a
+        target=\\\"_blank\\\" href=\\\"https://www.benzinga.com/markets/equities/24/06/39452342/bp-eyes-biofuel-dominance-in-brazil-with-expansion-plans-report\\\"
+        rel=\\\"noreferrer noopener\\\">stake in BP Bunge Bioenergia</a>.</p>\\n\\n\\n\\n<p>Investors
+        can gain exposure to the stock via&nbsp;<strong>Direxion Hydrogen ETF&nbsp;</strong>(ARCA:&nbsp;HJEN)&nbsp;and&nbsp;<strong>First
+        Trust Exchange-Traded Fund IV FT Energy Income Partners Strategy ETF</strong>
+        (ARCA:&nbsp;EIPX).</p>\\n\\n\\n\\n<p><strong>Price Action</strong>: BP shares
+        closed lower by 1.00% at $35.72 on Wednesday.</p>\\n\\n\\n\\n<p><strong><em>Disclaimer:</em></strong><em>
+        This content was partially produced with the help of AI tools and was reviewed
+        and published by Benzinga editors.</em></p>\",\"url\":\"https://www.benzinga.com/markets/equities/24/06/39519449/is-bp-bailing-on-green-reportedly-shifts-gears-from-renewables-to-oil-and-gas\",\"image\":[{\"size\":\"thumb\",\"url\":\"https://cdn.benzinga.com/files/imagecache/250x187xUP/images/story/2024/06/27/BP-Logo.png\"},{\"size\":\"small\",\"url\":\"https://cdn.benzinga.com/files/imagecache/1024x768xUP/images/story/2024/06/27/BP-Logo.png\"},{\"size\":\"large\",\"url\":\"https://cdn.benzinga.com/files/imagecache/2048x1536xUP/images/story/2024/06/27/BP-Logo.png\"}],\"channels\":[{\"name\":\"Equities\"},{\"name\":\"Large
+        Cap\"},{\"name\":\"News\"},{\"name\":\"Media\"}],\"stocks\":[{\"name\":\"BP\"}],\"tags\":[{\"name\":\"AI
+        Generated\"},{\"name\":\"Briefs\"},{\"name\":\"Eurasia\"},{\"name\":\"Stories
+        That Matter\"}]},{\"id\":39519448,\"author\":\"Benzinga Newsdesk\",\"created\":\"Thu,
+        27 Jun 2024 05:52:51 -0400\",\"updated\":\"Thu, 27 Jun 2024 05:52:51 -0400\",\"title\":\"Piper
+        Sandler Initiates Coverage On Dynatrace with Neutral Rating, Announces Price
+        Target of $50\",\"teaser\":\"Piper Sandler  analyst Rob Owens   initiates
+        coverage on Dynatrace (NYSE:DT) with a Neutral rating and announces Price
+        Target of $50.\",\"body\":\"Piper Sandler  analyst Rob Owens   initiates coverage
+        on Dynatrace (NYSE:<a class=\\\"ticker\\\" href=\\\"https://www.benzinga.com/stock/DT#NYSE\\\">DT</a>)
+        with a Neutral rating and announces Price Target of $50.\",\"url\":\"https://www.benzinga.com/news/24/06/39519448/piper-sandler-initiates-coverage-on-dynatrace-with-neutral-rating-announces-price-target-of-50\",\"image\":[],\"channels\":[{\"name\":\"News\"},{\"name\":\"Price
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openbb_platform/providers/benzinga/tests/test_benzinga_fetchers.py

@@ -0,0 +1,63 @@
+"""Test the Benzinga fetchers."""
+
+import pytest
+from openbb_benzinga.models.analyst_search import BenzingaAnalystSearchFetcher
+from openbb_benzinga.models.company_news import BenzingaCompanyNewsFetcher
+from openbb_benzinga.models.price_target import BenzingaPriceTargetFetcher
+from openbb_benzinga.models.world_news import BenzingaWorldNewsFetcher
+from openbb_core.app.service.user_service import UserService
+
+test_credentials = UserService().default_user_settings.credentials.model_dump(
+    mode="json"
+)
+
+
+@pytest.fixture(scope="module")
+def vcr_config():
+    """VCR configuration."""
+    return {
+        "filter_headers": [("User-Agent", None)],
+        "filter_query_parameters": [
+            ("token", "MOCK_TOKEN"),
+        ],
+    }
+
+
+@pytest.mark.record_http
+def test_benzinga_world_news_fetcher(credentials=test_credentials):
+    """Test the world news fetcher."""
+    params = {"limit": 20}
+
+    fetcher = BenzingaWorldNewsFetcher()
+    result = fetcher.test(params, credentials)
+    assert result is None
+
+
+@pytest.mark.record_http
+def test_benzinga_company_news_fetcher(credentials=test_credentials):
+    """Test the company news fetcher."""
+    params = {"symbol": "AAPL,MSFT", "limit": 20}
+
+    fetcher = BenzingaCompanyNewsFetcher()
+    result = fetcher.test(params, credentials)
+    assert result is None
+
+
+@pytest.mark.record_http
+def test_benzinga_price_target_fetcher(credentials=test_credentials):
+    """Test the price target fetcher."""
+    params = {"symbol": "AAPL"}
+
+    fetcher = BenzingaPriceTargetFetcher()
+    result = fetcher.test(params, credentials)
+    assert result is None
+
+
+@pytest.mark.record_http
+def test_benzinga_analyst_search_fetcher(credentials=test_credentials):
+    """Test the analyst search fetcher."""
+    params = {"firm_name": "Barclays"}
+
+    fetcher = BenzingaAnalystSearchFetcher()
+    result = fetcher.test(params, credentials)
+    assert result is None

openbb_platform/providers/biztoc/README.md

@@ -0,0 +1,14 @@
+# OpenBB Biztoc Provider
+
+This extension integrates the Biztoc data provider
+into the OpenBB Platform.
+
+## Installation
+
+To install the extension, run the following command in this folder:
+
+```bash
+pip install openbb-biztoc
+```
+
+Documentation available [here](https://docs.openbb.co/platform/developer_guide/contributing).

openbb_platform/providers/biztoc/__init__.py

@@ -0,0 +1 @@
+"""Biztoc provider."""

openbb_platform/providers/biztoc/openbb_biztoc/__init__.py

@@ -0,0 +1,25 @@
+"""Biztoc provider module."""
+
+from openbb_biztoc.models.world_news import BiztocWorldNewsFetcher
+from openbb_core.provider.abstract.provider import Provider
+
+biztoc_provider = Provider(
+    name="biztoc",
+    website="https://api.biztoc.com",
+    description="""BizToc uses Rapid API for its REST API.
+You may sign up for your free account at https://rapidapi.com/thma/api/biztoc.
+
+The Base URL for all requests is:
+
+    https://biztoc.p.rapidapi.com/
+
+If you're not a developer but would still like to use Biztoc outside of the main website,
+we've partnered with OpenBB, allowing you to pull in BizToc's news stream in their Terminal.""",
+    credentials=["api_key"],
+    fetcher_dict={
+        "WorldNews": BiztocWorldNewsFetcher,
+    },
+    repr_name="BizToc",
+    deprecated_credentials={"API_BIZTOC_TOKEN": "biztoc_api_key"},
+    instructions="The BizToc API is hosted on RapidAPI. To set up, go to: https://rapidapi.com/thma/api/biztoc.\n\n![biztoc0](https://github.com/marban/OpenBBTerminal/assets/18151143/04cdd423-f65e-4ad8-ad5a-4a59b0f5ddda)\n\nIn the top right, select 'Sign Up'. After answering some questions, you will be prompted to select one of their plans.\n\n![biztoc1](https://github.com/marban/OpenBBTerminal/assets/18151143/9f3b72ea-ded7-48c5-aa33-bec5c0de8422)\n\nAfter signing up, navigate back to https://rapidapi.com/thma/api/biztoc. If you are logged in, you will see a header called X-RapidAPI-Key.\n\n![biztoc2](https://github.com/marban/OpenBBTerminal/assets/18151143/0f3b6c91-07e0-447a-90cd-a9e23522929f)",  # noqa: E501  pylint: disable=line-too-long
+)

openbb_platform/providers/biztoc/openbb_biztoc/models/__init__.py

@@ -0,0 +1 @@
+"""Biztoc Provider models."""

openbb_platform/providers/biztoc/openbb_biztoc/models/world_news.py

@@ -0,0 +1,158 @@
+"""Biztoc World News Model."""
+
+# pylint: disable=unused-argument
+
+from typing import Any, Optional, Union
+from warnings import warn
+
+from openbb_core.app.model.abstract.error import OpenBBError
+from openbb_core.provider.abstract.fetcher import Fetcher
+from openbb_core.provider.standard_models.world_news import (
+    WorldNewsData,
+    WorldNewsQueryParams,
+)
+from openbb_core.provider.utils.errors import UnauthorizedError
+from pydantic import Field, field_validator
+
+
+class BiztocWorldNewsQueryParams(WorldNewsQueryParams):
+    """Biztoc World News Query."""
+
+    term: Optional[str] = Field(
+        description="Search term to filter articles by. This overrides all other filters.",
+        default=None,
+    )
+    source: Optional[str] = Field(
+        description="Filter by a specific publisher. Only valid when filter is set to source.",
+        default=None,
+    )
+
+
+class BiztocWorldNewsData(WorldNewsData):
+    """Biztoc World News Data."""
+
+    __alias_dict__ = {
+        "date": "published",
+        "text": "body",
+        "images": "img",
+    }
+
+    images: Optional[list[dict[str, str]]] = Field(
+        description="Images for the article.", default=None
+    )
+    tags: Optional[list[str]] = Field(description="Tags for the article.", default=None)
+    score: Optional[float] = Field(
+        description="Search relevance score for the article.", default=None
+    )
+
+    @field_validator("date", "updated", mode="before", check_fields=False)
+    @classmethod
+    def date_validate(cls, v):
+        """Return formatted datetime."""
+        # pylint: disable=import-outside-toplevel
+        from pandas import to_datetime
+
+        return (
+            to_datetime(v, utc=True)
+            .tz_convert("America/New_York")
+            .strftime("%Y-%m-%d %H:%M:%S%z")
+        )
+
+    @field_validator("title")
+    @classmethod
+    def title_validate(cls, v):
+        """Strip empty title text."""
+        return v.strip() if v else None
+
+
+class BiztocWorldNewsFetcher(
+    Fetcher[
+        BiztocWorldNewsQueryParams,
+        list[BiztocWorldNewsData],
+    ]
+):
+    """Transform the query, extract and transform the data from the Biztoc endpoints."""
+
+    @staticmethod
+    def transform_query(params: dict[str, Any]) -> BiztocWorldNewsQueryParams:
+        """Transform the query."""
+        if params.get("start_date") or params.get("end_date"):
+            warn("start_date and end_date are not supported for this endpoint.")
+        return BiztocWorldNewsQueryParams(**params)
+
+    @staticmethod
+    async def aextract_data(
+        query: BiztocWorldNewsQueryParams,
+        credentials: Optional[dict[str, str]],
+        **kwargs: Any,
+    ) -> list[dict]:
+        """Extract the data from the Biztoc endpoint."""
+        # pylint: disable=import-outside-toplevel
+        from openbb_core.provider.utils.helpers import amake_request, make_request
+
+        async def response_callback(response, _):
+            res = await response.json()
+            if isinstance(res, dict) and "message" in res:
+                if "subscribed" in res["message"].lower():
+                    raise UnauthorizedError(
+                        f"Unauthorized Biztoc request -> {res['message']}"
+                    )
+                raise OpenBBError(res["message"])
+
+            return await response.json()
+
+        api_key = credentials.get("biztoc_api_key") if credentials else ""
+        headers = {
+            "X-RapidAPI-Key": f"{api_key}",
+            "X-RapidAPI-Host": "biztoc.p.rapidapi.com",
+            "Accept": "application/json",
+            "Accept-Encoding": "gzip",
+        }
+        base_url = "https://biztoc.p.rapidapi.com/"
+        url = ""
+        response: Union[list, dict] = []
+        if query.term:
+            query.term = query.term.replace(" ", "%20")
+            url = base_url + f"search?q={query.term}"
+            response = await amake_request(
+                url, headers=headers, response_callback=response_callback
+            )
+        elif query.source is not None:
+            sources_response = make_request(
+                "https://biztoc.p.rapidapi.com/sources",
+                headers=headers,
+            ).json()
+            sources = [source["id"] for source in sources_response]
+            if query.source.lower() not in sources:
+                raise OpenBBError(
+                    f"{query.source} not a valid source. Valid sources: {sources}"
+                )
+            url = base_url + f"news/source/{query.source.lower()}"
+            response = await amake_request(
+                url, headers=headers, response_callback=response_callback
+            )
+        else:
+            url1 = base_url + "news/latest"
+            response = await amake_request(
+                url1, headers=headers, response_callback=response_callback
+            )
+
+        return response  # type: ignore
+
+    @staticmethod
+    def transform_data(
+        query: BiztocWorldNewsQueryParams, data: list[dict], **kwargs: Any
+    ) -> list[BiztocWorldNewsData]:
+        """Transform the data to the standard format."""
+        results: list[BiztocWorldNewsData] = []
+        for item in data:
+            item.pop("id", None)
+            item.pop("uid", None)
+            item.pop("body_preview", None)
+            item.pop("site", None)
+            item.pop("domain", None)
+            images = item.pop("img", [])
+            if images:
+                item["images"] = images if isinstance(images, list) else [images]
+            results.append(BiztocWorldNewsData.model_validate(item))
+        return results

openbb_platform/providers/biztoc/openbb_biztoc/utils/__init__.py

@@ -0,0 +1 @@
+"""Biztoc utils."""

openbb_platform/providers/biztoc/pyproject.toml

@@ -0,0 +1,19 @@
+[tool.poetry]
+name = "openbb-biztoc"
+version = "1.4.2"
+description = "Biztoc Provider for OpenBB Platform"
+authors = ["OpenBB Team <hello@openbb.co>"]
+license = "AGPL-3.0-only"
+readme = "README.md"
+packages = [{ include = "openbb_biztoc" }]
+
+[tool.poetry.dependencies]
+python = ">=3.9.21,<3.13"
+openbb-core = "^1.4.6"
+
+[build-system]
+requires = ["poetry-core"]
+build-backend = "poetry.core.masonry.api"
+
+[tool.poetry.plugins."openbb_provider_extension"]
+biztoc = "openbb_biztoc:biztoc_provider"

openbb_platform/providers/biztoc/tests/__init__.py

@@ -0,0 +1 @@
+"""Biztoc Provider tests."""

openbb_platform/providers/biztoc/tests/record/http/test_biztoc_fetchers/test_biztoc_world_news_fetcher_urllib3_v1.yaml

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+      X-RateLimit-rapid-free-plans-hard-limit-Limit:
+      - '500000'
+      X-RateLimit-rapid-free-plans-hard-limit-Remaining:
+      - '499961'
+      X-RateLimit-rapid-free-plans-hard-limit-Reset:
+      - '1620568'
+      alt-svc:
+      - h3=":443"; ma=86400
+      permissions-policy:
+      - browsing-topics=()
+      referrer-policy:
+      - strict-origin-when-cross-origin
+      rndr-id:
+      - 96769602-78bc-4d9d
+      x-content-type-options:
+      - nosniff
+      x-render-origin-server:
+      - gunicorn
+    status:
+      code: 200
+      message: OK
+- request:
+    body: null
+    headers:
+      Accept:
+      - application/json
+      Accept-Encoding:
+      - gzip
+      X-RapidAPI-Host:
+      - biztoc.p.rapidapi.com
+      X-RapidAPI-Key:
+      - MOCK_API_KEY
+    method: GET
+    uri: https://biztoc.p.rapidapi.com/news/source/bloomberg
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+    headers:
+      CF-Cache-Status:
+      - DYNAMIC
+      CF-RAY:
+      - 8d46253e7fd558ba-IAD
+      Cache-Control:
+      - no-store, no-cache, must-revalidate, max-age=0
+      Connection:
+      - keep-alive
+      Content-Encoding:
+      - gzip
+      Content-Type:
+      - application/json
+      Date:
+      - Fri, 18 Oct 2024 05:32:01 GMT
+      NEL:
+      - '{"success_fraction":0,"report_to":"cf-nel","max_age":604800}'
+      Report-To:
+      - '{"endpoints":[{"url":"https:\/\/a.nel.cloudflare.com\/report\/v4?s=1jncDmrg1XfuP0IcLzSdFqxnDMUXcq%2FYLEq7Y47JCzrfHGKMIYKTdVDqO5wAJ1CDVG8lCorUMgO5Aw5pGQ4cBY8eGoB%2FI0iTPcN%2FHHf9%2Bz3zMUu9I%2FdQYPbfHmI%3D"}],"group":"cf-nel","max_age":604800}'
+      Server:
+      - RapidAPI-1.2.8
+      Strict-Transport-Security:
+      - max-age=31556926; includeSubDomains
+      Transfer-Encoding:
+      - chunked
+      Vary:
+      - Accept-Encoding, Cookie
+      X-RapidAPI-Region:
+      - AWS - us-east-1
+      X-RapidAPI-Request-Id:
+      - c9f0a6fb613c5c0a2361b3f48bba6dcc7bc83feaa827675cb22eb492b1669872
+      X-RapidAPI-Version:
+      - 1.2.8
+      X-RateLimit-Requests-Limit:
+      - '2000'
+      X-RateLimit-Requests-Remaining:
+      - '1913'
+      X-RateLimit-Requests-Reset:
+      - '1620568'
+      X-RateLimit-rapid-free-plans-hard-limit-Limit:
+      - '500000'
+      X-RateLimit-rapid-free-plans-hard-limit-Remaining:
+      - '499960'
+      X-RateLimit-rapid-free-plans-hard-limit-Reset:
+      - '1620568'
+      alt-svc:
+      - h3=":443"; ma=86400
+      permissions-policy:
+      - browsing-topics=()
+      referrer-policy:
+      - strict-origin-when-cross-origin
+      rndr-id:
+      - 8911030f-1e15-4bb9
+      x-content-type-options:
+      - nosniff
+      x-render-origin-server:
+      - gunicorn
+    status:
+      code: 200
+      message: OK
+version: 1

openbb_platform/providers/biztoc/tests/test_biztoc_fetchers.py

@@ -0,0 +1,33 @@
+"""Tests for the Biztoc fetchers."""
+
+import pytest
+from openbb_biztoc.models.world_news import BiztocWorldNewsFetcher
+from openbb_core.app.service.user_service import UserService
+
+test_credentials = UserService().default_user_settings.credentials.model_dump(
+    mode="json"
+)
+
+
+@pytest.fixture(scope="module")
+def vcr_config():
+    """VCR configuration."""
+    return {
+        "filter_headers": [
+            ("X-RapidAPI-Key", "MOCK_API_KEY"),
+            ("User-Agent", None),
+        ],
+        "filter_query_parameters": [
+            ("apikey", "MOCK_API_KEY"),
+        ],
+    }
+
+
+@pytest.mark.record_http
+def test_biztoc_world_news_fetcher(credentials=test_credentials):
+    """Test the Biztoc World News fetcher."""
+    params = {"source": "bloomberg"}
+
+    fetcher = BiztocWorldNewsFetcher()
+    result = fetcher.test(params, credentials)
+    assert result is None

openbb_platform/providers/bls/README.md

@@ -0,0 +1,19 @@
+# BLS Provider Extension
+
+This extension integrates the BLS data provider into the OpenBB Platform.
+
+## Installation
+
+To install this extension from PyPI:
+
+```console
+pip install openbb-bls
+```
+
+To install the extension locally, run the following command in this folder:
+
+```console
+poetry install
+```
+
+Documentation available [here](https://docs.openbb.co/platform/developer_guide/contributing).

openbb_platform/providers/bls/__init__.py

@@ -0,0 +1 @@
+"""BLS Provider Extension."""

openbb_platform/providers/bls/openbb_bls/__init__.py

@@ -0,0 +1,21 @@
+"""BLS Provider Module."""
+
+from openbb_bls.models.search import BlsSearchFetcher
+from openbb_bls.models.series import BlsSeriesFetcher
+from openbb_core.provider.abstract.provider import Provider
+
+bls_provider = Provider(
+    name="bls",
+    website="https://www.bls.gov/developers/api_signature_v2.htm",
+    description="The Bureau of Labor Statistics' (BLS) Public Data Application Programming Interface (API)"
+    + " gives the public access to economic data from all BLS programs."
+    + " It is the Bureau's hope that talented developers and programmers will use the BLS Public Data API to create"
+    + " original, inventive applications with published BLS data.",
+    credentials=["api_key"],
+    fetcher_dict={
+        "BlsSearch": BlsSearchFetcher,
+        "BlsSeries": BlsSeriesFetcher,
+    },
+    repr_name="Bureau of Labor Statistics' (BLS) Public Data API",
+    instructions="Sign up for a free API key here: https://data.bls.gov/registrationEngine/",
+)

openbb_platform/providers/bls/openbb_bls/assets/__init__.py

@@ -0,0 +1 @@
+"""BLS Provider Static Assets."""

openbb_platform/providers/bls/openbb_bls/assets/bed_codes.json

@@ -0,0 +1,221 @@
+{
+    "bd": {
+        "msa_code": {
+            "00000": "National"
+        },
+        "state_code": {
+            "00": "U.S. totals",
+            "01": "Alabama",
+            "02": "Alaska",
+            "04": "Arizona",
+            "05": "Arkansas",
+            "06": "California",
+            "08": "Colorado",
+            "09": "Connecticut",
+            "10": "Delaware",
+            "11": "District of Columbia",
+            "12": "Florida",
+            "13": "Georgia",
+            "15": "Hawaii",
+            "16": "Idaho",
+            "17": "Illinois",
+            "18": "Indiana",
+            "19": "Iowa",
+            "20": "Kansas",
+            "21": "Kentucky",
+            "22": "Louisiana",
+            "23": "Maine",
+            "24": "Maryland",
+            "25": "Massachusetts",
+            "26": "Michigan",
+            "27": "Minnesota",
+            "28": "Mississippi",
+            "29": "Missouri",
+            "30": "Montana",
+            "31": "Nebraska",
+            "32": "Nevada",
+            "33": "New Hampshire",
+            "34": "New Jersey",
+            "35": "New Mexico",
+            "36": "New York",
+            "37": "North Carolina",
+            "38": "North Dakota",
+            "39": "Ohio",
+            "40": "Oklahoma",
+            "41": "Oregon",
+            "42": "Pennsylvania",
+            "44": "Rhode Island",
+            "45": "South Carolina",
+            "46": "South Dakota",
+            "47": "Tennessee",
+            "48": "Texas",
+            "49": "Utah",
+            "50": "Vermont",
+            "51": "Virginia",
+            "53": "Washington",
+            "54": "West Virginia",
+            "55": "Wisconsin",
+            "56": "Wyoming",
+            "72": "Puerto Rico",
+            "78": "Virgin Islands"
+        },
+        "county_code": {
+            "000": "National"
+        },
+        "industry_code": {
+            "000000": "Total private",
+            "100000": "Goods-producing",
+            "100010": "Natural resources and mining",
+            "100020": "Construction",
+            "100030": "Manufacturing",
+            "200000": "Service-providing",
+            "200010": "Wholesale trade",
+            "200020": "Retail trade",
+            "200030": "Transportation and warehousing",
+            "200040": "Utilities",
+            "200050": "Information",
+            "200060": "Financial activities",
+            "200070": "Professional and business services",
+            "200080": "Education and health services",
+            "200090": "Leisure and hospitality",
+            "200100": "Other services (except public administration)",
+            "300111": "Crop production",
+            "300112": "Animal production and aquaculture",
+            "300113": "Forestry and logging",
+            "300114": "Hunting, fishing, and trapping",
+            "300115": "Support activities for agriculture and forestry",
+            "300211": "Oil and gas extraction",
+            "300212": "Mining (except oil and gas)",
+            "300213": "Support activities for mining",
+            "300236": "Construction of buildings",
+            "300237": "Heavy and civil engineering construction",
+            "300238": "Specialty trade contractors",
+            "300311": "Food manufacturing",
+            "300312": "Beverage and tobacco product manufacturing",
+            "300313": "Textile mills",
+            "300314": "Textile product mills",
+            "300315": "Apparel manufacturing",
+            "300316": "Leather and allied product manufacturing",
+            "300321": "Wood product manufacturing",
+            "300322": "Paper Manufacturing",
+            "300323": "Printing and related support activities",
+            "300324": "Petroleum and coal products manufacturing",
+            "300325": "Chemical manufacturing",
+            "300326": "Plastics and rubber products manufacturing",
+            "300327": "Nonmetallic mineral product manufacturing",
+            "300331": "Primary metal manufacturing",
+            "300332": "Fabricated metal product manufacturing",
+            "300333": "Machinery manufacturing",
+            "300334": "Computer and electronic product manufacturing",
+            "300335": "Electrical equipment, appliance, and component manufacturing",
+            "300336": "Transportation equipment manufacturing",
+            "300337": "Furniture and related product manufacturing",
+            "300339": "Miscellaneous manufacturing",
+            "300423": "Merchant wholesalers, durable goods",
+            "300424": "Merchant wholesalers, nondurable goods",
+            "300425": "Wholesale trade agents and brokers",
+            "300441": "Motor vehicle and parts dealers",
+            "300444": "Building material and garden equipment and supplies dealers",
+            "300445": "Food and beverage stores",
+            "300481": "Air transportation",
+            "300483": "Water transportation",
+            "300484": "Truck transportation",
+            "300485": "Transit and ground passenger transportation",
+            "300486": "Pipeline transportation",
+            "300487": "Scenic and sightseeing transportation",
+            "300488": "Support activities for transportation",
+            "300492": "Couriers and messengers",
+            "300493": "Warehousing and storage",
+            "300512": "Motion picture and sound recording industries",
+            "300517": "Telecommunications",
+            "300518": "Computing infracstructure providers, data processing, web hosting, and related services",
+            "300519": "Web search portals, libraries, archives, and other information services",
+            "300522": "Credit intermediation and related activities",
+            "300523": "Securities, commodity contracts, and other financial investments and related activities",
+            "300524": "Insurance carriers and related activities",
+            "300525": "Funds, trusts, and other financial vehicles",
+            "300531": "Real estate",
+            "300532": "Rental and leasing services",
+            "300533": "Lessors of nonfinancial intangible assets (except copyrighted works)",
+            "300541": "Professional, scientific, and technical services",
+            "300551": "Management of companies and enterprises",
+            "300561": "Administrative and support services",
+            "300562": "Waste management and remediation services",
+            "300611": "Educational services",
+            "300621": "Ambulatory health care services",
+            "300622": "Hospitals",
+            "300623": "Nursing and residential care facilities",
+            "300624": "Social assistance",
+            "300711": "Performing arts, spectator sports, and related industries",
+            "300712": "Museums, historical sites, and similar institutions",
+            "300713": "Amusement, gambling, and recreation industries",
+            "300721": "Accommodation",
+            "300722": "Food services and drinking places",
+            "300811": "Repair and maintenance",
+            "300812": "Personal and laundry services",
+            "300813": "Religious, grantmaking, civic, professional, and similar organizations"
+        },
+        "unitanalysis_code": {
+            "1": "Establishment"
+        },
+        "dataelement_code": {
+            "1": "Employment",
+            "2": "Number of Establishments"
+        },
+        "sizeclass_code": {
+            "00": "All size classes",
+            "01": "1 to 4 employees",
+            "02": "5 to 9 employees",
+            "03": "10 to 19 employees",
+            "04": "20 to 49 employees",
+            "05": "50 to 99 employees",
+            "06": "100 to 249 employees",
+            "07": "250 to 499 employees",
+            "08": "500 to 999 employees",
+            "09": "1,000 or more employees",
+            "10": "1 job",
+            "11": "2 jobs",
+            "12": "3 jobs",
+            "13": "4 jobs",
+            "14": "5 jobs",
+            "15": "6 jobs",
+            "16": "7 jobs",
+            "17": "8 jobs",
+            "18": "9 jobs",
+            "19": "10 jobs",
+            "20": "11-14 jobs",
+            "21": "15-19 jobs",
+            "22": "20-24 jobs",
+            "23": "25-29 jobs",
+            "24": "30-39 jobs",
+            "25": "40-49 jobs",
+            "26": "50-74 jobs",
+            "27": "75-99 jobs",
+            "28": "100 or more jobs",
+            "31": "1 to 4 jobs",
+            "32": "5 to 19 jobs",
+            "33": "20 or more jobs"
+        },
+        "dataclass_code": {
+            "01": "Gross Job Gains",
+            "02": "Expansions",
+            "03": "Openings",
+            "04": "Gross Job Losses",
+            "05": "Contractions",
+            "06": "Closings",
+            "07": "Establishment Births",
+            "08": "Establishment Deaths"
+        },
+        "ratelevel_code": {
+            "L": "Level",
+            "R": "Rate"
+        },
+        "ownership_code": {
+            "5": "Private Sector"
+        },
+        "footnote_code": {
+            "1": "Total private includes unclassified sector, not shown separately",
+            "2": "An administrative event occurred during this quarter"
+        }
+    }
+}

openbb_platform/providers/bls/openbb_bls/assets/bed_series.xz

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:16f64094e475d68e6e932ff196b719a5e762beb702b8d1ab1ecb3d4ab07646c7
+size 170164

openbb_platform/providers/bls/openbb_bls/assets/cpi_codes.json

@@ -0,0 +1,1199 @@
+{
+    "ap": {
+        "area_code": {
+            "0000": "U.S. city average",
+            "0100": "Northeast",
+            "0110": "New England",
+            "0120": "Middle Atlantic",
+            "0200": "Midwest",
+            "0230": "East North Central",
+            "0240": "West North Central",
+            "0300": "South",
+            "0350": "South Atlantic",
+            "0360": "East South Central",
+            "0370": "West South Central",
+            "0400": "West",
+            "0480": "Mountain",
+            "0490": "Pacific",
+            "A104": "Pittsburgh, PA",
+            "A105": "Buffalo-Niagara Falls, NY",
+            "A106": "Scranton, PA",
+            "A210": "Cleveland-Akron, OH",
+            "A212": "Milwaukee-Racine, WI",
+            "A213": "Cincinnati-Hamilton, OH-KY-IN",
+            "A214": "Kansas City, MO-KS",
+            "A311": "Washington-Baltimore, DC-MD-VA-WV",
+            "A315": "Washington, DC-MD-VA",
+            "A317": "Baltimore, MD",
+            "A421": "Los Angeles-Riverside-Orange County, CA",
+            "A425": "Portland-Salem, OR-WA",
+            "B000": "City size B",
+            "B100": "Northeast size B",
+            "B200": "North Central size B",
+            "B300": "South size B",
+            "B400": "West size B",
+            "C000": "City size C",
+            "C100": "Northeast size C",
+            "C200": "North Central size C",
+            "C300": "South size C",
+            "C400": "West size C",
+            "D000": "Size Class D",
+            "D100": "Northeast - Size Class D",
+            "D200": "Midwest - Size Class D",
+            "D300": "South - Size Class D",
+            "D400": "West - Size Class D",
+            "N000": "Size Class B/C",
+            "N100": "Northeast - Size Class B/C",
+            "N200": "Midwest - Size Class B/C",
+            "N300": "South - Size Class B/C",
+            "N400": "West - Size Class B/C",
+            "S000": "Size Class A",
+            "S100": "Northeast - Size Class A",
+            "S11A": "Boston-Cambridge-Newton, MA-NH",
+            "S12A": "New York-Newark-Jersey City, NY-NJ-PA",
+            "S12B": "Philadelphia-Camden-Wilmington, PA-NJ-DE-MD",
+            "S200": "Midwest - Size Class A",
+            "S23A": "Chicago-Naperville-Elgin, IL-IN-WI",
+            "S23B": "Detroit-Warren-Dearborn, MI",
+            "S24A": "Minneapolis-St.Paul-Bloomington, MN-WI",
+            "S24B": "St. Louis, MO-IL",
+            "S300": "South - Size Class A",
+            "S35A": "Washington-Arlington-Alexandria, DC-VA-MD-WV",
+            "S35B": "Miami-Fort Lauderdale-West Palm Beach, FL",
+            "S35C": "Atlanta-Sandy Springs-Roswell, GA",
+            "S35D": "Tampa-St. Petersburg-Clearwater, FL",
+            "S35E": "Baltimore-Columbia-Towson, MD",
+            "S37A": "Dallas-Fort Worth-Arlington, TX",
+            "S37B": "Houston-The Woodlands-Sugar Land, TX",
+            "S400": "West - Size Class A",
+            "S48A": "Phoenix-Mesa-Scottsdale, AZ",
+            "S48B": "Denver-Aurora-Lakewood, CO",
+            "S49A": "Los Angeles-Long Beach-Anaheim, CA",
+            "S49B": "San Francisco-Oakland-Hayward, CA",
+            "S49C": "Riverside-San Bernardino-Ontario, CA",
+            "S49D": "Seattle-Tacoma-Bellevue WA",
+            "S49E": "San Diego-Carlsbad, CA",
+            "S49F": "Urban Hawaii",
+            "S49G": "Urban Alaska"
+        },
+        "item_code": {
+            "701111": "Flour, white, all purpose, per lb. (453.6 gm)",
+            "701311": "Rice, white, long grain, precooked (cost per pound/453.6 grams)",
+            "701312": "Rice, white, long grain, uncooked, per lb. (453.6 gm)",
+            "701321": "Spaghetti (cost per pound/453.6 grams)",
+            "701322": "Spaghetti and macaroni, per lb. (453.6 gm)",
+            "702111": "Bread, white, pan, per lb. (453.6 gm)",
+            "702112": "Bread, French, per lb. (453.6 gm)",
+            "702211": "Bread, rye, pan (cost per pound/453.6 grams)",
+            "702212": "Bread, whole wheat, pan, per lb. (453.6 gm)",
+            "702213": "Bread, wheat blend, pan (cost per pound/453.6 grams)",
+            "702221": "Rolls, hamburger (cost per pound/453.6 grams)",
+            "702411": "Cupcakes, chocolate (cost per pound/453.6 grams)",
+            "702421": "Cookies, chocolate chip, per lb. (453.6 gm)",
+            "702611": "Crackers, soda, salted, per lb. (453.6 gm)",
+            "703111": "Ground chuck, 100% beef, per lb. (453.6 gm)",
+            "703112": "Ground beef, 100% beef, per lb. (453.6 gm)",
+            "703113": "Ground beef, lean and extra lean, per lb. (453.6 gm)",
+            "703211": "Chuck roast, USDA Choice, bone-in, per lb. (453.6 gm)",
+            "703212": "Chuck roast, graded and ungraded, excluding USDA Prime and Choice, per lb. (453.6 gm)",
+            "703213": "Chuck roast, USDA Choice, boneless, per lb. (453.6 gm)",
+            "703311": "Round roast, USDA Choice, boneless, per lb. (453.6 gm)",
+            "703312": "Round roast, graded and ungraded, excluding USDA Prime and Choice, per lb. (453.6 gm)",
+            "703411": "Rib roast, USDA Choice, bone-in, per lb. (453.6 gm)",
+            "703421": "Steak, chuck, U.S. choice, bone-in (cost per pound/453.6 grams)",
+            "703422": "Steak, T-Bone, USDA Choice, bone-in, per lb. (453.6 gm)",
+            "703423": "Steak, porterhouse, U.S. choice, bone-in (cost per pound/453.6 grams)",
+            "703425": "Steak, rib eye, USDA Choice, boneless, per lb. (453.6 gm)",
+            "703431": "Short ribs, any primal source, bone-in, per lb. (453.6 gm)",
+            "703432": "Beef for stew, boneless, per lb. (453.6 gm)",
+            "703511": "Steak, round, USDA Choice, boneless, per lb. (453.6 gm)",
+            "703512": "Steak, round, graded and ungraded, excluding USDA Prime and Choice, per lb. (453.6 gm)",
+            "703611": "Steak, sirloin, USDA Choice, bone-in, per lb. (453.6 gm)",
+            "703612": "Steak, sirloin, graded and ungraded, excluding USDA Prime and Choice, per lb. (453.6 gm)",
+            "703613": "Steak, sirloin, USDA Choice, boneless, per lb. (453.6 gm)",
+            "704111": "Bacon, sliced, per lb. (453.6 gm)",
+            "704211": "Chops, center cut, bone-in, per lb. (453.6 gm)",
+            "704212": "Chops, boneless, per lb. (453.6 gm)",
+            "704311": "Ham, rump or shank half, bone-in, smoked,per lb. (453.6 gm)",
+            "704312": "Ham, boneless, excluding canned, per lb. (453.6 gm)",
+            "704313": "Ham, rump portion, bone-in, smoked (cost per pound/453.6 grams)",
+            "704314": "Ham, shank portion, bone-in, smoked (cost per pound/453.6 grams)",
+            "704321": "Ham, canned, 3 or 5 lbs, per lb. (453.6 gm)",
+            "704411": "Pork shoulder roast, blade boston, bone-in (cost per pound/453.6 grams)",
+            "704412": "Pork sirloin roast, bone-in (cost per pound/453.6 grams)",
+            "704413": "Shoulder picnic, bone-in, smoked, per lb. (453.6 gm)",
+            "704421": "Sausage, fresh, loose, per lb. (453.6 gm)",
+            "705111": "Frankfurters, all meat or all beef, per lb. (453.6 gm)",
+            "705121": "Bologna, all beef or mixed, per lb. (453.6 gm)",
+            "705141": "Beef liver (cost per pound/453.6 grams)",
+            "705142": "Lamb and mutton, bone-in, per lb. (453.6 gm)",
+            "706111": "Chicken, fresh, whole, per lb. (453.6 gm)",
+            "706211": "Chicken breast, bone-in, per lb. (453.6 gm)",
+            "706212": "Chicken legs, bone-in, per lb. (453.6 gm)",
+            "706311": "Turkey, frozen, whole, per lb. (453.6 gm)",
+            "707111": "Tuna, light, chunk, per lb. (453.6 gm)",
+            "708111": "Eggs, grade A, large, per doz.",
+            "708112": "Eggs, grade AA, large, per doz.",
+            "709111": "Milk, fresh, whole, fortified, per 1/2 gal. (1.9 lit)",
+            "709112": "Milk, fresh, whole, fortified, per gal. (3.8 lit)",
+            "709211": "Milk, fresh, skim (cost per one-half gallon/1.9 liters)",
+            "709212": "Milk, fresh, low fat, per 1/2 gal. (1.9 lit)",
+            "709213": "Milk, fresh, low fat, per gal. (3.8 lit)",
+            "710111": "Butter, salted, grade AA, stick, per lb. (453.6 gm)",
+            "710122": "Yogurt, natural, fruit flavored, per 8 oz. (226.8 gm)",
+            "710211": "American processed cheese, per lb. (453.6 gm)",
+            "710212": "Cheddar cheese, natural, per lb. (453.6 gm)",
+            "710411": "Ice cream, prepackaged, bulk, regular, per 1/2 gal. (1.9 lit)",
+            "711111": "Apples, Red Delicious, per lb. (453.6 gm)",
+            "711211": "Bananas, per lb. (453.6 gm)",
+            "711311": "Oranges, Navel, per lb. (453.6 gm)",
+            "711312": "Oranges, Valencia, per lb. (453.6 gm)",
+            "711411": "Grapefruit, per lb. (453.6 gm)",
+            "711412": "Lemons, per lb. (453.6 gm)",
+            "711413": "Pears, Anjou, per lb. (453.6 gm)",
+            "711414": "Peaches, per lb. (453.6 gm)",
+            "711415": "Strawberries, dry pint, per 12 oz. (340.2 gm)",
+            "711416": "Grapes, Emperor or Tokay (cost per pound/453.6 grams)",
+            "711417": "Grapes, Thompson Seedless, per lb. (453.6 gm)",
+            "711418": "Cherries, per lb. (453.6 gm)",
+            "712111": "Potatoes, white (cost per pound/453.6 grams)",
+            "712112": "Potatoes, white, per lb. (453.6 gm)",
+            "712211": "Lettuce, iceberg, per lb. (453.6 gm)",
+            "712311": "Tomatoes, field grown, per lb. (453.6 gm)",
+            "712401": "Cabbage, per lb. (453.6 gm)",
+            "712402": "Celery, per lb. (453.6 gm)",
+            "712403": "Carrots, short trimmed and topped, per lb. (453.6 gm)",
+            "712404": "Onions, dry yellow, per lb. (453.6 gm)",
+            "712405": "Onions, green scallions (cost per pound/453.6 grams)",
+            "712406": "Peppers, sweet, per lb. (453.6 gm)",
+            "712407": "Corn on the cob, per lb. (453.6 gm)",
+            "712408": "Radishes (cost per pound/453.6 grams)",
+            "712409": "Cucumbers, per lb. (453.6 gm)",
+            "712410": "Beans, green, snap (cost per pound/453.6 grams)",
+            "712411": "Mushrooms (cost per pound/453.6 grams)",
+            "712412": "Broccoli, per lb. (453.6 gm)",
+            "713111": "Orange juice, frozen concentrate, 12 oz. can, per 16 oz. (473.2 ml)",
+            "713311": "Apple Sauce, any variety, all sizes, per lb. (453.6 gm)",
+            "713312": "Peaches, any variety, all sizes, per lb. (453.6 gm)",
+            "714111": "Potatoes, frozen, French fried, per lb. (453.6 gm)",
+            "714221": "Corn, canned, any style, all sizes, per lb. (453.6 gm)",
+            "714231": "Tomatoes, canned, whole, per lb. (453.6 gm)",
+            "714232": "Tomatoes, canned, any type, all sizes,  per lb. (453.6 gm)",
+            "714233": "Beans, dried, any type, all sizes, per lb. (453.6 gm)",
+            "715111": "Hard candy, solid (cost per pound/453.6 grams)",
+            "715211": "Sugar, white, all sizes, per lb. (453.6 gm)",
+            "715212": "Sugar, white, 33-80 oz. pkg, per lb. (453.6 gm)",
+            "715311": "Jelly (cost per pound/453.6 grams)",
+            "716111": "Margarine, vegetable oil blends, stick (cost per pound/453.6 grams)",
+            "716113": "Margarine, vegetable oil blends, soft, tubs (cost per pound/453.6 grams)",
+            "716114": "Margarine, stick, per lb. (453.6 gm)",
+            "716116": "Margarine, soft, tubs, per lb. (453.6 gm)",
+            "716121": "Shortening, vegetable oil blends, per lb. (453.6 gm)",
+            "716141": "Peanut butter, creamy, all sizes, per lb. (453.6 gm)",
+            "717111": "Cola, non-diet, return bottles, 6 or 8 pack (cost per 16 ounces/473.2 ml)",
+            "717112": "Cola, non diet, return bottles, 24-40 ounce (cost per 16 ounces/473.2 ml)",
+            "717113": "Cola, nondiet, cans, 72 oz. 6 pk., per 16 oz. (473.2 ml)",
+            "717114": "Cola, nondiet, per 2 liters (67.6 oz)",
+            "717311": "Coffee, 100%, ground roast, all sizes, per lb. (453.6 gm)",
+            "717312": "Coffee, 100%, ground roast, 13.1-20 oz. can, per lb. (453.6 gm)",
+            "717324": "Coffee, instant, plain, regular, 6.1-14 ounce (cost per 16 ounces/453.6 grams)",
+            "717325": "Coffee, freeze dried, regular, all sizes (cost per 16 ounces/453.6 grams)",
+            "717326": "Coffee, freeze dried, decaf., all sizes (cost per 16 ounces/453.6 grams)",
+            "717327": "Coffee, instant, plain, regular, all sizes, per lb. (453.6 gm)",
+            "717411": "Coffee, instant, plain, 9.1-14 ounce (cost per 16 ounces/453.6 grams)",
+            "717412": "Coffee, instant, plain, 3.1-6 ounce (cost per 16 ounces/453.6 grams)",
+            "717413": "Coffee, freeze dried, plain, 3.1-9 ounce (cost per 16 ounces/453.6 grams)",
+            "718311": "Potato chips, per 16 oz.",
+            "718631": "Pork and beans, canned (cost per 16 ounces/453.6 grams)",
+            "720111": "Malt beverages, all types, all sizes, any origin, per 16 oz. (473.2 ml)",
+            "720211": "Bourbon whiskey, 375 ml-1.75 liter (cost per 25.4 ounces/750 ml)",
+            "720221": "Vodka, domestic, 375 ml-1.75 liter (cost per 25.4 ounces/750 ml)",
+            "720222": "Vodka, all types, all sizes, any origin, per 1 liter (33.8 oz)",
+            "720311": "Wine, red and white table, all sizes, any origin, per 1 liter (33.8 oz)",
+            "72511": "Fuel oil #2 per gallon (3.785 liters)",
+            "72601": "Utility (piped) gas - 40 therms",
+            "72610": "Electricity per KWH",
+            "72611": "Utility (piped) gas - 100 therms",
+            "72620": "Utility (piped) gas per therm",
+            "72621": "Electricity per 500 KWH",
+            "74712": "Gasoline, leaded regular (cost per gallon/3.8 liters)",
+            "74713": "Gasoline, leaded premium (cost per gallon/3.8 liters)",
+            "74714": "Gasoline, unleaded regular, per gallon/3.785 liters",
+            "74715": "Gasoline, unleaded midgrade, per gallon/3.785 liters",
+            "74716": "Gasoline, unleaded premium, per gallon/3.785 liters",
+            "74717": "Automotive diesel fuel, per gallon/3.785 liters",
+            "7471A": "Gasoline, all types, per gallon/3.785 liters",
+            "FC1101": "All uncooked ground beef, per lb. (453.6 gm)",
+            "FC2101": "All Uncooked Beef Roasts, per lb. (453.6 gm)",
+            "FC3101": "All Uncooked Beef Steaks, per lb. (453.6 gm)",
+            "FC4101": "All Uncooked Other Beef (Excluding Veal), per lb. (453.6 gm)",
+            "FD2101": "All Ham (Excluding Canned Ham and Luncheon Slices), per lb. (453.6 gm)",
+            "FD3101": "All Pork Chops, per lb. (453.6 gm)",
+            "FD4101": "All Other Pork (Excluding Canned Ham and Luncheon Slices), per lb. (453.6 gm)",
+            "FF1101": "Chicken breast, boneless, per lb. (453.6 gm)",
+            "FJ1101": "Milk, fresh, low-fat, reduced fat, skim, per gal. (3.8 lit)",
+            "FJ4101": "Yogurt, per 8 oz. (226.8 gm)",
+            "FL2101": "Lettuce, romaine, per lb. (453.6 gm)",
+            "FN1101": "All soft drinks, per 2 liters (67.6 oz)",
+            "FN1102": "All soft drinks, 12 pk, 12 oz., cans, per 12 oz. (354.9 ml)",
+            "FS1101": "Butter, stick, per lb. (453.6 gm)"
+        }
+    },
+    "cu": {
+        "area_code": {
+            "0000": "U.S. city average",
+            "0100": "Northeast",
+            "0110": "New England",
+            "0120": "Middle Atlantic",
+            "0200": "Midwest",
+            "0230": "East North Central",
+            "0240": "West North Central",
+            "0300": "South",
+            "0350": "South Atlantic",
+            "0360": "East South Central",
+            "0370": "West South Central",
+            "0400": "West",
+            "0480": "Mountain",
+            "0490": "Pacific",
+            "A104": "Pittsburgh, PA",
+            "A210": "Cleveland-Akron, OH",
+            "A212": "Milwaukee-Racine, WI",
+            "A213": "Cincinnati-Hamilton, OH-KY-IN",
+            "A214": "Kansas City, MO-KS",
+            "A311": "Washington-Baltimore, DC-MD-VA-WV",
+            "A421": "Los Angeles-Riverside-Orange County, CA",
+            "A425": "Portland-Salem, OR-WA",
+            "D000": "Size Class D",
+            "D200": "Midwest - Size Class D",
+            "D300": "South - Size Class D",
+            "N000": "Size Class B/C",
+            "N100": "Northeast - Size Class B/C",
+            "N200": "Midwest - Size Class B/C",
+            "N300": "South - Size Class B/C",
+            "N400": "West - Size Class B/C",
+            "S000": "Size Class A",
+            "S100": "Northeast - Size Class A",
+            "S11A": "Boston-Cambridge-Newton, MA-NH",
+            "S12A": "New York-Newark-Jersey City, NY-NJ-PA",
+            "S12B": "Philadelphia-Camden-Wilmington, PA-NJ-DE-MD",
+            "S200": "Midwest - Size Class A",
+            "S23A": "Chicago-Naperville-Elgin, IL-IN-WI",
+            "S23B": "Detroit-Warren-Dearborn, MI",
+            "S24A": "Minneapolis-St.Paul-Bloomington, MN-WI",
+            "S24B": "St. Louis, MO-IL",
+            "S300": "South - Size Class A",
+            "S35A": "Washington-Arlington-Alexandria, DC-VA-MD-WV",
+            "S35B": "Miami-Fort Lauderdale-West Palm Beach, FL",
+            "S35C": "Atlanta-Sandy Springs-Roswell, GA",
+            "S35D": "Tampa-St. Petersburg-Clearwater, FL",
+            "S35E": "Baltimore-Columbia-Towson, MD",
+            "S37A": "Dallas-Fort Worth-Arlington, TX",
+            "S37B": "Houston-The Woodlands-Sugar Land, TX",
+            "S400": "West - Size Class A",
+            "S48A": "Phoenix-Mesa-Scottsdale, AZ",
+            "S48B": "Denver-Aurora-Lakewood, CO",
+            "S49A": "Los Angeles-Long Beach-Anaheim, CA",
+            "S49B": "San Francisco-Oakland-Hayward, CA",
+            "S49C": "Riverside-San Bernardino-Ontario, CA",
+            "S49D": "Seattle-Tacoma-Bellevue WA",
+            "S49E": "San Diego-Carlsbad, CA",
+            "S49F": "Urban Hawaii",
+            "S49G": "Urban Alaska"
+        },
+        "item_code": {
+            "AA0": "All items - old base",
+            "AA0R": "Purchasing power of the consumer dollar - old base",
+            "SA0": "All items",
+            "SA0E": "Energy",
+            "SA0L1": "All items less food",
+            "SA0L12": "All items less food and shelter",
+            "SA0L12E": "All items less food, shelter, and energy",
+            "SA0L12E4": "All items less food, shelter, energy, and used cars and trucks",
+            "SA0L1E": "All items less food and energy",
+            "SA0L2": "All items less shelter",
+            "SA0L5": "All items less medical care",
+            "SA0LE": "All items less energy",
+            "SA0R": "Purchasing power of the consumer dollar",
+            "SA311": "Apparel less footwear",
+            "SAA": "Apparel",
+            "SAA1": "Men's and boys' apparel",
+            "SAA2": "Women's and girls' apparel",
+            "SAC": "Commodities",
+            "SACE": "Energy commodities",
+            "SACL1": "Commodities less food",
+            "SACL11": "Commodities less food and beverages",
+            "SACL1E": "Commodities less food and energy commodities",
+            "SACL1E4": "Commodities less food, energy, and used cars and trucks",
+            "SAD": "Durables",
+            "SAE": "Education and communication",
+            "SAE1": "Education",
+            "SAE2": "Communication",
+            "SAE21": "Information and information processing",
+            "SAEC": "Education and communication commodities",
+            "SAES": "Education and communication services",
+            "SAF": "Food and beverages",
+            "SAF1": "Food",
+            "SAF11": "Food at home",
+            "SAF111": "Cereals and bakery products",
+            "SAF112": "Meats, poultry, fish, and eggs",
+            "SAF1121": "Meats, poultry, and fish",
+            "SAF11211": "Meats",
+            "SAF113": "Fruits and vegetables",
+            "SAF1131": "Fresh fruits and vegetables",
+            "SAF114": "Nonalcoholic beverages and beverage materials",
+            "SAF115": "Other food at home",
+            "SAF116": "Alcoholic beverages",
+            "SAG": "Other goods and services",
+            "SAG1": "Personal care",
+            "SAGC": "Other goods",
+            "SAGS": "Other personal services",
+            "SAH": "Housing",
+            "SAH1": "Shelter",
+            "SAH2": "Fuels and utilities",
+            "SAH21": "Household energy",
+            "SAH3": "Household furnishings and operations",
+            "SAH31": "Household furnishings and supplies",
+            "SAM": "Medical care",
+            "SAM1": "Medical care commodities",
+            "SAM2": "Medical care services",
+            "SAN": "Nondurables",
+            "SAN1D": "Domestically produced farm food",
+            "SANL1": "Nondurables less food",
+            "SANL11": "Nondurables less food and beverages",
+            "SANL113": "Nondurables less food, beverages, and apparel",
+            "SANL13": "Nondurables less food and apparel",
+            "SAR": "Recreation",
+            "SARC": "Recreation commodities",
+            "SARS": "Recreation services",
+            "SAS": "Services",
+            "SAS24": "Utilities and public transportation",
+            "SAS2RS": "Rent of shelter",
+            "SAS367": "Other services",
+            "SAS4": "Transportation services",
+            "SASL2RS": "Services less rent of shelter",
+            "SASL5": "Services less medical care services",
+            "SASLE": "Services less energy services",
+            "SAT": "Transportation",
+            "SAT1": "Private transportation",
+            "SATCLTB": "Transportation commodities less motor fuel",
+            "SEAA": "Men's apparel",
+            "SEAA01": "Men's suits, sport coats, and outerwear",
+            "SEAA02": "Men's underwear, nightwear, swimwear and accessories",
+            "SEAA03": "Men's shirts and sweaters",
+            "SEAA04": "Men's pants and shorts",
+            "SEAB": "Boys' apparel",
+            "SEAC": "Women's apparel",
+            "SEAC01": "Women's outerwear",
+            "SEAC02": "Women's dresses",
+            "SEAC03": "Women's suits and separates",
+            "SEAC04": "Women's underwear, nightwear, swimwear and accessories",
+            "SEAD": "Girls' apparel",
+            "SEAE": "Footwear",
+            "SEAE01": "Men's footwear",
+            "SEAE02": "Boys' and girls' footwear",
+            "SEAE03": "Women's footwear",
+            "SEAF": "Infants' and toddlers' apparel",
+            "SEAG": "Jewelry and watches",
+            "SEAG01": "Watches",
+            "SEAG02": "Jewelry",
+            "SEEA": "Educational books and supplies",
+            "SEEB": "Tuition, other school fees, and childcare",
+            "SEEB01": "College tuition and fees",
+            "SEEB02": "Elementary and high school tuition and fees",
+            "SEEB03": "Day care and preschool",
+            "SEEB04": "Technical and business school tuition and fees",
+            "SEEC": "Postage and delivery services",
+            "SEEC01": "Postage",
+            "SEEC02": "Delivery services",
+            "SEED": "Telephone services",
+            "SEED03": "Wireless telephone services",
+            "SEED04": "Residential telephone services",
+            "SEEE": "Information technology, hardware and services",
+            "SEEE01": "Computers, peripherals, and smart home assistants",
+            "SEEE02": "Computer software and accessories",
+            "SEEE03": "Internet services and electronic information providers",
+            "SEEE04": "Telephone hardware, calculators, and other consumer information items",
+            "SEEEC": "Information technology commodities",
+            "SEFA": "Cereals and cereal products",
+            "SEFA01": "Flour and prepared flour mixes",
+            "SEFA02": "Breakfast cereal",
+            "SEFA03": "Rice, pasta, cornmeal",
+            "SEFB": "Bakery products",
+            "SEFB01": "Bread",
+            "SEFB02": "Fresh biscuits, rolls, muffins",
+            "SEFB03": "Cakes, cupcakes, and cookies",
+            "SEFB04": "Other bakery products",
+            "SEFC": "Beef and veal",
+            "SEFC01": "Uncooked ground beef",
+            "SEFC02": "Uncooked beef roasts",
+            "SEFC03": "Uncooked beef steaks",
+            "SEFC04": "Uncooked other beef and veal",
+            "SEFD": "Pork",
+            "SEFD01": "Bacon, breakfast sausage, and related products",
+            "SEFD02": "Ham",
+            "SEFD03": "Pork chops",
+            "SEFD04": "Other pork including roasts, steaks, and ribs",
+            "SEFE": "Other meats",
+            "SEFF": "Poultry",
+            "SEFF01": "Chicken",
+            "SEFF02": "Other uncooked poultry including turkey",
+            "SEFG": "Fish and seafood",
+            "SEFG01": "Fresh fish and seafood",
+            "SEFG02": "Processed fish and seafood",
+            "SEFH": "Eggs",
+            "SEFJ": "Dairy and related products",
+            "SEFJ01": "Milk",
+            "SEFJ02": "Cheese and related products",
+            "SEFJ03": "Ice cream and related products",
+            "SEFJ04": "Other dairy and related products",
+            "SEFK": "Fresh fruits",
+            "SEFK01": "Apples",
+            "SEFK02": "Bananas",
+            "SEFK03": "Citrus fruits",
+            "SEFK04": "Other fresh fruits",
+            "SEFL": "Fresh vegetables",
+            "SEFL01": "Potatoes",
+            "SEFL02": "Lettuce",
+            "SEFL03": "Tomatoes",
+            "SEFL04": "Other fresh vegetables",
+            "SEFM": "Processed fruits and vegetables",
+            "SEFM01": "Canned fruits and vegetables",
+            "SEFM02": "Frozen fruits and vegetables",
+            "SEFM03": "Other processed fruits and vegetables including dried",
+            "SEFN": "Juices and nonalcoholic drinks",
+            "SEFN01": "Carbonated drinks",
+            "SEFN02": "Frozen noncarbonated juices and drinks",
+            "SEFN03": "Nonfrozen noncarbonated juices and drinks",
+            "SEFP": "Beverage materials including coffee and tea",
+            "SEFP01": "Coffee",
+            "SEFP02": "Other beverage materials including tea",
+            "SEFR": "Sugar and sweets",
+            "SEFR01": "Sugar and sugar substitutes",
+            "SEFR02": "Candy and chewing gum",
+            "SEFR03": "Other sweets",
+            "SEFS": "Fats and oils",
+            "SEFS01": "Butter and margarine",
+            "SEFS02": "Salad dressing",
+            "SEFS03": "Other fats and oils including peanut butter",
+            "SEFT": "Other foods",
+            "SEFT01": "Soups",
+            "SEFT02": "Frozen and freeze dried prepared foods",
+            "SEFT03": "Snacks",
+            "SEFT04": "Spices, seasonings, condiments, sauces",
+            "SEFT05": "Baby food and formula",
+            "SEFT06": "Other miscellaneous foods",
+            "SEFV": "Food away from home",
+            "SEFV01": "Full service meals and snacks",
+            "SEFV02": "Limited service meals and snacks",
+            "SEFV03": "Food at employee sites and schools",
+            "SEFV04": "Food from vending machines and mobile vendors",
+            "SEFV05": "Other food away from home",
+            "SEFW": "Alcoholic beverages at home",
+            "SEFW01": "Beer, ale, and other malt beverages at home",
+            "SEFW02": "Distilled spirits at home",
+            "SEFW03": "Wine at home",
+            "SEFX": "Alcoholic beverages away from home",
+            "SEGA": "Tobacco and smoking products",
+            "SEGA01": "Cigarettes",
+            "SEGA02": "Tobacco products other than cigarettes",
+            "SEGB": "Personal care products",
+            "SEGB01": "Hair, dental, shaving, and miscellaneous personal care products",
+            "SEGB02": "Cosmetics, perfume, bath, nail preparations and implements",
+            "SEGC": "Personal care services",
+            "SEGC01": "Haircuts and other personal care services",
+            "SEGD": "Miscellaneous personal services",
+            "SEGD01": "Legal services",
+            "SEGD02": "Funeral expenses",
+            "SEGD03": "Laundry and dry cleaning services",
+            "SEGD04": "Apparel services other than laundry and dry cleaning",
+            "SEGD05": "Financial services",
+            "SEGE": "Miscellaneous personal goods",
+            "SEHA": "Rent of primary residence",
+            "SEHB": "Lodging away from home",
+            "SEHB01": "Housing at school, excluding board",
+            "SEHB02": "Other lodging away from home including hotels and motels",
+            "SEHC": "Owners' equivalent rent of residences",
+            "SEHC01": "Owners' equivalent rent of primary residence",
+            "SEHD": "Tenants' and household insurance",
+            "SEHE": "Fuel oil and other fuels",
+            "SEHE01": "Fuel oil",
+            "SEHE02": "Propane, kerosene, and firewood",
+            "SEHF": "Energy services",
+            "SEHF01": "Electricity",
+            "SEHF02": "Utility (piped) gas service",
+            "SEHG": "Water and sewer and trash collection services",
+            "SEHG01": "Water and sewerage maintenance",
+            "SEHG02": "Garbage and trash collection",
+            "SEHH": "Window and floor coverings and other linens",
+            "SEHH01": "Floor coverings",
+            "SEHH02": "Window coverings",
+            "SEHH03": "Other linens",
+            "SEHJ": "Furniture and bedding",
+            "SEHJ01": "Bedroom furniture",
+            "SEHJ02": "Living room, kitchen, and dining room furniture",
+            "SEHJ03": "Other furniture",
+            "SEHK": "Appliances",
+            "SEHK01": "Major appliances",
+            "SEHK02": "Other appliances",
+            "SEHL": "Other household equipment and furnishings",
+            "SEHL01": "Clocks, lamps, and decorator items",
+            "SEHL02": "Indoor plants and flowers",
+            "SEHL03": "Dishes and flatware",
+            "SEHL04": "Nonelectric cookware and tableware",
+            "SEHM": "Tools, hardware, outdoor equipment and supplies",
+            "SEHM01": "Tools, hardware and supplies",
+            "SEHM02": "Outdoor equipment and supplies",
+            "SEHN": "Housekeeping supplies",
+            "SEHN01": "Household cleaning products",
+            "SEHN02": "Household paper products",
+            "SEHN03": "Miscellaneous household products",
+            "SEHP": "Household operations",
+            "SEHP01": "Domestic services",
+            "SEHP02": "Gardening and lawncare services",
+            "SEHP03": "Moving, storage, freight expense",
+            "SEHP04": "Repair of household items",
+            "SEMC": "Professional services",
+            "SEMC01": "Physicians' services",
+            "SEMC02": "Dental services",
+            "SEMC03": "Eyeglasses and eye care",
+            "SEMC04": "Services by other medical professionals",
+            "SEMD": "Hospital and related services",
+            "SEMD01": "Hospital services",
+            "SEMD02": "Nursing homes and adult day services",
+            "SEMD03": "Care of invalids and elderly at home",
+            "SEME": "Health insurance",
+            "SEMF": "Medicinal drugs",
+            "SEMF01": "Prescription drugs",
+            "SEMF02": "Nonprescription drugs",
+            "SEMG": "Medical equipment and supplies",
+            "SERA": "Video and audio",
+            "SERA01": "Televisions",
+            "SERA02": "Cable, satellite, and live streaming television service",
+            "SERA03": "Other video equipment",
+            "SERA04": "Purchase, subscription, and rental of video",
+            "SERA05": "Audio equipment",
+            "SERA06": "Recorded music and music subscriptions",
+            "SERAC": "Video and audio products",
+            "SERAS": "Video and audio services",
+            "SERB": "Pets, pet products and services",
+            "SERB01": "Pets and pet products",
+            "SERB02": "Pet services including veterinary",
+            "SERC": "Sporting goods",
+            "SERC01": "Sports vehicles including bicycles",
+            "SERC02": "Sports equipment",
+            "SERD": "Photography",
+            "SERD01": "Photographic equipment and supplies",
+            "SERD02": "Photographers and photo processing",
+            "SERE": "Other recreational goods",
+            "SERE01": "Toys",
+            "SERE02": "Sewing machines, fabric and supplies",
+            "SERE03": "Music instruments and accessories",
+            "SERF": "Other recreation services",
+            "SERF01": "Club membership for shopping clubs, fraternal, or other organizations, or participant sports fees",
+            "SERF02": "Admissions",
+            "SERF03": "Fees for lessons or instructions",
+            "SERG": "Recreational reading materials",
+            "SERG01": "Newspapers and magazines",
+            "SERG02": "Recreational books",
+            "SETA": "New and used motor vehicles",
+            "SETA01": "New vehicles",
+            "SETA02": "Used cars and trucks",
+            "SETA03": "Leased cars and trucks",
+            "SETA04": "Car and truck rental",
+            "SETB": "Motor fuel",
+            "SETB01": "Gasoline (all types)",
+            "SETB02": "Other motor fuels",
+            "SETC": "Motor vehicle parts and equipment",
+            "SETC01": "Tires",
+            "SETC02": "Vehicle accessories other than tires",
+            "SETD": "Motor vehicle maintenance and repair",
+            "SETD01": "Motor vehicle body work",
+            "SETD02": "Motor vehicle maintenance and servicing",
+            "SETD03": "Motor vehicle repair",
+            "SETE": "Motor vehicle insurance",
+            "SETF": "Motor vehicle fees",
+            "SETF01": "State motor vehicle registration and license fees",
+            "SETF03": "Parking and other fees",
+            "SETG": "Public transportation",
+            "SETG01": "Airline fares",
+            "SETG02": "Other intercity transportation",
+            "SETG03": "Intracity transportation",
+            "SS01031": "Rice",
+            "SS02011": "White bread",
+            "SS02021": "Bread other than white",
+            "SS02041": "Fresh cakes and cupcakes",
+            "SS02042": "Cookies",
+            "SS02063": "Fresh sweetrolls, coffeecakes, doughnuts",
+            "SS0206A": "Crackers, bread, and cracker products",
+            "SS0206B": "Frozen and refrigerated bakery products, pies, tarts, turnovers",
+            "SS04011": "Bacon and related products",
+            "SS04012": "Breakfast sausage and related products",
+            "SS04031": "Ham, excluding canned",
+            "SS05011": "Frankfurters",
+            "SS05014": "Lamb and organ meats",
+            "SS05015": "Lamb and mutton",
+            "SS0501A": "Lunchmeats",
+            "SS06011": "Fresh whole chicken",
+            "SS06021": "Fresh and frozen chicken parts",
+            "SS07011": "Shelf stable fish and seafood",
+            "SS07021": "Frozen fish and seafood",
+            "SS09011": "Fresh whole milk",
+            "SS09021": "Fresh milk other than whole",
+            "SS10011": "Butter",
+            "SS11031": "Oranges, including tangerines",
+            "SS13031": "Canned fruits",
+            "SS14011": "Frozen vegetables",
+            "SS14021": "Canned vegetables",
+            "SS14022": "Dried beans, peas, and lentils",
+            "SS16011": "Margarine",
+            "SS16014": "Peanut butter",
+            "SS17031": "Roasted coffee",
+            "SS17032": "Instant coffee",
+            "SS18041": "Salt and other seasonings and spices",
+            "SS18042": "Olives, pickles, relishes",
+            "SS18043": "Sauces and gravies",
+            "SS1804B": "Other condiments",
+            "SS18064": "Prepared salads",
+            "SS20021": "Whiskey at home",
+            "SS20022": "Distilled spirits, excluding whiskey, at home",
+            "SS20051": "Beer, ale, and other malt beverages away from home",
+            "SS20052": "Wine away from home",
+            "SS20053": "Distilled spirits away from home",
+            "SS27051": "Land-line interstate toll calls",
+            "SS27061": "Land-line intrastate toll calls",
+            "SS30021": "Laundry equipment",
+            "SS31022": "Video discs and other media",
+            "SS31023": "Video game hardware, software and accessories",
+            "SS33032": "Stationery, stationery supplies, gift wrap",
+            "SS45011": "New cars",
+            "SS4501A": "New cars and trucks",
+            "SS45021": "New trucks",
+            "SS45031": "New motorcycles",
+            "SS47014": "Gasoline, unleaded regular",
+            "SS47015": "Gasoline, unleaded midgrade",
+            "SS47016": "Gasoline, unleaded premium",
+            "SS47021": "Motor oil, coolant, and fluids",
+            "SS48021": "Vehicle parts and equipment other than tires",
+            "SS52051": "Parking fees and tolls",
+            "SS53021": "Intercity bus fare",
+            "SS53022": "Intercity train fare",
+            "SS53023": "Ship fare",
+            "SS53031": "Intracity mass transit",
+            "SS5702": "Inpatient hospital services",
+            "SS5703": "Outpatient hospital services",
+            "SS61011": "Toys, games, hobbies and playground equipment",
+            "SS61021": "Film and photographic supplies",
+            "SS61023": "Photographic equipment",
+            "SS61031": "Pet food",
+            "SS61032": "Purchase of pets, pet supplies, accessories",
+            "SS62011": "Automobile service clubs",
+            "SS62031": "Admission to movies, theaters, and concerts",
+            "SS62032": "Admission to sporting events",
+            "SS62051": "Photographer fees",
+            "SS62052": "Photo Processing",
+            "SS62053": "Pet services",
+            "SS62054": "Veterinarian services",
+            "SS62055": "Subscription and rental of video and video games",
+            "SS68021": "Checking account and other bank services",
+            "SS68023": "Tax return preparation and other accounting fees",
+            "SSEA011": "College textbooks",
+            "SSEE041": "Smartphones",
+            "SSFV031A": "Food at elementary and secondary schools",
+            "SSGE013": "Infants' equipment",
+            "SSHJ031": "Infants' furniture"
+        },
+        "base_code": {
+            "A": "Alternate",
+            "S": "Current"
+        }
+    },
+    "cw": {
+        "area_code": {
+            "0000": "U.S. city average",
+            "0100": "Northeast",
+            "0110": "New England",
+            "0120": "Middle Atlantic",
+            "0200": "Midwest",
+            "0230": "East North Central",
+            "0240": "West North Central",
+            "0300": "South",
+            "0350": "South Atlantic",
+            "0360": "East South Central",
+            "0370": "West South Central",
+            "0400": "West",
+            "0480": "Mountain",
+            "0490": "Pacific",
+            "A104": "Pittsburgh, PA",
+            "A210": "Cleveland-Akron, OH",
+            "A212": "Milwaukee-Racine, WI",
+            "A213": "Cincinnati-Hamilton, OH-KY-IN",
+            "A214": "Kansas City, MO-KS",
+            "A311": "Washington-Baltimore, DC-MD-VA-WV",
+            "A421": "Los Angeles-Riverside-Orange County, CA",
+            "A425": "Portland-Salem, OR-WA",
+            "D000": "Size Class D",
+            "D200": "Midwest - Size Class D",
+            "D300": "South - Size Class D",
+            "N000": "Size Class B/C",
+            "N100": "Northeast - Size Class B/C",
+            "N200": "Midwest - Size Class B/C",
+            "N300": "South - Size Class B/C",
+            "N400": "West - Size Class B/C",
+            "S000": "Size Class A",
+            "S100": "Northeast - Size Class A",
+            "S11A": "Boston-Cambridge-Newton, MA-NH",
+            "S12A": "New York-Newark-Jersey City, NY-NJ-PA",
+            "S12B": "Philadelphia-Camden-Wilmington, PA-NJ-DE-MD",
+            "S200": "Midwest - Size Class A",
+            "S23A": "Chicago-Naperville-Elgin, IL-IN-WI",
+            "S23B": "Detroit-Warren-Dearborn, MI",
+            "S24A": "Minneapolis-St.Paul-Bloomington, MN-WI",
+            "S24B": "St. Louis, MO-IL",
+            "S300": "South - Size Class A",
+            "S35A": "Washington-Arlington-Alexandria, DC-VA-MD-WV",
+            "S35B": "Miami-Fort Lauderdale-West Palm Beach, FL",
+            "S35C": "Atlanta-Sandy Springs-Roswell, GA",
+            "S35D": "Tampa-St. Petersburg-Clearwater, FL",
+            "S35E": "Baltimore-Columbia-Towson, MD",
+            "S37A": "Dallas-Fort Worth-Arlington, TX",
+            "S37B": "Houston-The Woodlands-Sugar Land, TX",
+            "S400": "West - Size Class A",
+            "S48A": "Phoenix-Mesa-Scottsdale, AZ",
+            "S48B": "Denver-Aurora-Lakewood, CO",
+            "S49A": "Los Angeles-Long Beach-Anaheim, CA",
+            "S49B": "San Francisco-Oakland-Hayward, CA",
+            "S49C": "Riverside-San Bernardino-Ontario, CA",
+            "S49D": "Seattle-Tacoma-Bellevue WA",
+            "S49E": "San Diego-Carlsbad, CA",
+            "S49F": "Urban Hawaii",
+            "S49G": "Urban Alaska"
+        },
+        "item_code": {
+            "AA0": "All items - old base",
+            "AA0R": "Purchasing power of the consumer dollar - old base",
+            "SA0": "All items",
+            "SA0E": "Energy",
+            "SA0L1": "All items less food",
+            "SA0L1E": "All items less food and energy",
+            "SA0L2": "All items less shelter",
+            "SA0L5": "All items less medical care",
+            "SA0LE": "All items less energy",
+            "SA0R": "Purchasing power of the consumer dollar",
+            "SA311": "Apparel less footwear",
+            "SAA": "Apparel",
+            "SAA1": "Men's and boys' apparel",
+            "SAA2": "Women's and girls' apparel",
+            "SAC": "Commodities",
+            "SACE": "Energy commodities",
+            "SACL1": "Commodities less food",
+            "SACL11": "Commodities less food and beverages",
+            "SACL1E": "Commodities less food and energy commodities",
+            "SAD": "Durables",
+            "SAE": "Education and communication",
+            "SAE1": "Education",
+            "SAE2": "Communication",
+            "SAE21": "Information and information processing",
+            "SAEC": "Education and communication commodities",
+            "SAES": "Education and communication services",
+            "SAF": "Food and beverages",
+            "SAF1": "Food",
+            "SAF11": "Food at home",
+            "SAF111": "Cereals and bakery products",
+            "SAF112": "Meats, poultry, fish, and eggs",
+            "SAF1121": "Meats, poultry, and fish",
+            "SAF11211": "Meats",
+            "SAF113": "Fruits and vegetables",
+            "SAF1131": "Fresh fruits and vegetables",
+            "SAF114": "Nonalcoholic beverages and beverage materials",
+            "SAF115": "Other food at home",
+            "SAF116": "Alcoholic beverages",
+            "SAG": "Other goods and services",
+            "SAG1": "Personal care",
+            "SAGC": "Other goods",
+            "SAGS": "Other personal services",
+            "SAH": "Housing",
+            "SAH1": "Shelter",
+            "SAH2": "Fuels and utilities",
+            "SAH21": "Household energy",
+            "SAH3": "Household furnishings and operations",
+            "SAH31": "Household furnishings and supplies",
+            "SAM": "Medical care",
+            "SAM1": "Medical care commodities",
+            "SAM2": "Medical care services",
+            "SAN": "Nondurables",
+            "SAN1D": "Domestically produced farm food",
+            "SANL1": "Nondurables less food",
+            "SANL11": "Nondurables less food and beverages",
+            "SANL113": "Nondurables less food, beverages, and apparel",
+            "SANL13": "Nondurables less food and apparel",
+            "SAR": "Recreation",
+            "SARC": "Recreation commodities",
+            "SARS": "Recreation services",
+            "SAS": "Services",
+            "SAS24": "Utilities and public transportation",
+            "SAS2RS": "Rent of shelter",
+            "SAS367": "Other services",
+            "SAS4": "Transportation services",
+            "SASL2RS": "Services less rent of shelter",
+            "SASL5": "Services less medical care services",
+            "SASLE": "Services less energy services",
+            "SAT": "Transportation",
+            "SAT1": "Private transportation",
+            "SATCLTB": "Transportation commodities less motor fuel",
+            "SEAA": "Men's apparel",
+            "SEAA01": "Men's suits, sport coats, and outerwear",
+            "SEAA02": "Men's underwear, nightwear, swimwear and accessories",
+            "SEAA03": "Men's shirts and sweaters",
+            "SEAA04": "Men's pants and shorts",
+            "SEAB": "Boys' apparel",
+            "SEAC": "Women's apparel",
+            "SEAC01": "Women's outerwear",
+            "SEAC02": "Women's dresses",
+            "SEAC03": "Women's suits and separates",
+            "SEAC04": "Women's underwear, nightwear, swimwear and accessories",
+            "SEAD": "Girls' apparel",
+            "SEAE": "Footwear",
+            "SEAE01": "Men's footwear",
+            "SEAE02": "Boys' and girls' footwear",
+            "SEAE03": "Women's footwear",
+            "SEAF": "Infants' and toddlers' apparel",
+            "SEAG": "Jewelry and watches",
+            "SEAG01": "Watches",
+            "SEAG02": "Jewelry",
+            "SEEA": "Educational books and supplies",
+            "SEEB": "Tuition, other school fees, and childcare",
+            "SEEB01": "College tuition and fees",
+            "SEEB02": "Elementary and high school tuition and fees",
+            "SEEB03": "Day care and preschool",
+            "SEEB04": "Technical and business school tuition and fees",
+            "SEEC": "Postage and delivery services",
+            "SEEC01": "Postage",
+            "SEEC02": "Delivery services",
+            "SEED": "Telephone services",
+            "SEED03": "Wireless telephone services",
+            "SEED04": "Residential telephone services",
+            "SEEE": "Information technology, hardware and services",
+            "SEEE01": "Computers, peripherals, and smart home assistants",
+            "SEEE02": "Computer software and accessories",
+            "SEEE03": "Internet services and electronic information providers",
+            "SEEE04": "Telephone hardware, calculators, and other consumer information items",
+            "SEEEC": "Information technology commodities",
+            "SEFA": "Cereals and cereal products",
+            "SEFA01": "Flour and prepared flour mixes",
+            "SEFA02": "Breakfast cereal",
+            "SEFA03": "Rice, pasta, cornmeal",
+            "SEFB": "Bakery products",
+            "SEFB01": "Bread",
+            "SEFB02": "Fresh biscuits, rolls, muffins",
+            "SEFB03": "Cakes, cupcakes, and cookies",
+            "SEFB04": "Other bakery products",
+            "SEFC": "Beef and veal",
+            "SEFC01": "Uncooked ground beef",
+            "SEFC02": "Uncooked beef roasts",
+            "SEFC03": "Uncooked beef steaks",
+            "SEFC04": "Uncooked other beef and veal",
+            "SEFD": "Pork",
+            "SEFD01": "Bacon, breakfast sausage, and related products",
+            "SEFD02": "Ham",
+            "SEFD03": "Pork chops",
+            "SEFD04": "Other pork including roasts, steaks, and ribs",
+            "SEFE": "Other meats",
+            "SEFF": "Poultry",
+            "SEFF01": "Chicken",
+            "SEFF02": "Other uncooked poultry including turkey",
+            "SEFG": "Fish and seafood",
+            "SEFG01": "Fresh fish and seafood",
+            "SEFG02": "Processed fish and seafood",
+            "SEFH": "Eggs",
+            "SEFJ": "Dairy and related products",
+            "SEFJ01": "Milk",
+            "SEFJ02": "Cheese and related products",
+            "SEFJ03": "Ice cream and related products",
+            "SEFJ04": "Other dairy and related products",
+            "SEFK": "Fresh fruits",
+            "SEFK01": "Apples",
+            "SEFK02": "Bananas",
+            "SEFK03": "Citrus fruits",
+            "SEFK04": "Other fresh fruits",
+            "SEFL": "Fresh vegetables",
+            "SEFL01": "Potatoes",
+            "SEFL02": "Lettuce",
+            "SEFL03": "Tomatoes",
+            "SEFL04": "Other fresh vegetables",
+            "SEFM": "Processed fruits and vegetables",
+            "SEFM01": "Canned fruits and vegetables",
+            "SEFM02": "Frozen fruits and vegetables",
+            "SEFM03": "Other processed fruits and vegetables including dried",
+            "SEFN": "Juices and nonalcoholic drinks",
+            "SEFN01": "Carbonated drinks",
+            "SEFN02": "Frozen noncarbonated juices and drinks",
+            "SEFN03": "Nonfrozen noncarbonated juices and drinks",
+            "SEFP": "Beverage materials including coffee and tea",
+            "SEFP01": "Coffee",
+            "SEFP02": "Other beverage materials including tea",
+            "SEFR": "Sugar and sweets",
+            "SEFR01": "Sugar and sugar substitutes",
+            "SEFR02": "Candy and chewing gum",
+            "SEFR03": "Other sweets",
+            "SEFS": "Fats and oils",
+            "SEFS01": "Butter and margarine",
+            "SEFS02": "Salad dressing",
+            "SEFS03": "Other fats and oils including peanut butter",
+            "SEFT": "Other foods",
+            "SEFT01": "Soups",
+            "SEFT02": "Frozen and freeze dried prepared foods",
+            "SEFT03": "Snacks",
+            "SEFT04": "Spices, seasonings, condiments, sauces",
+            "SEFT05": "Baby Food and Formula",
+            "SEFT06": "Other miscellaneous foods",
+            "SEFV": "Food away from home",
+            "SEFV01": "Full service meals and snacks",
+            "SEFV02": "Limited service meals and snacks",
+            "SEFV03": "Food at employee sites and schools",
+            "SEFV04": "Food from vending machines and mobile vendors",
+            "SEFV05": "Other food away from home",
+            "SEFW": "Alcoholic beverages at home",
+            "SEFW01": "Beer, ale, and other malt beverages at home",
+            "SEFW02": "Distilled spirits at home",
+            "SEFW03": "Wine at home",
+            "SEFX": "Alcoholic beverages away from home",
+            "SEGA": "Tobacco and smoking products",
+            "SEGA01": "Cigarettes",
+            "SEGA02": "Tobacco products other than cigarettes",
+            "SEGB": "Personal care products",
+            "SEGB01": "Hair, dental, shaving, and miscellaneous personal care products",
+            "SEGB02": "Cosmetics, perfume, bath, nail preparations and implements",
+            "SEGC": "Personal care services",
+            "SEGC01": "Haircuts and other personal care services",
+            "SEGD": "Miscellaneous personal services",
+            "SEGD01": "Legal services",
+            "SEGD02": "Funeral expenses",
+            "SEGD03": "Laundry and dry cleaning services",
+            "SEGD04": "Apparel services other than laundry and dry cleaning",
+            "SEGD05": "Financial services",
+            "SEGE": "Miscellaneous personal goods",
+            "SEHA": "Rent of primary residence",
+            "SEHB": "Lodging away from home",
+            "SEHB01": "Housing at school, excluding board",
+            "SEHB02": "Other lodging away from home including hotels and motels",
+            "SEHC": "Owners' equivalent rent of residences",
+            "SEHC01": "Owners' equivalent rent of primary residence",
+            "SEHD": "Tenants' and household insurance",
+            "SEHE": "Fuel oil and other fuels",
+            "SEHE01": "Fuel oil",
+            "SEHE02": "Propane, kerosene, and firewood",
+            "SEHF": "Energy services",
+            "SEHF01": "Electricity",
+            "SEHF02": "Utility (piped) gas service",
+            "SEHG": "Water and sewer and trash collection services",
+            "SEHG01": "Water and sewerage maintenance",
+            "SEHG02": "Garbage and trash collection",
+            "SEHH": "Window and floor coverings and other linens",
+            "SEHH01": "Floor coverings",
+            "SEHH02": "Window coverings",
+            "SEHH03": "Other linens",
+            "SEHJ": "Furniture and bedding",
+            "SEHJ01": "Bedroom furniture",
+            "SEHJ02": "Living room, kitchen, and dining room furniture",
+            "SEHJ03": "Other furniture",
+            "SEHK": "Appliances",
+            "SEHK01": "Major appliances",
+            "SEHK02": "Other appliances",
+            "SEHL": "Other household equipment and furnishings",
+            "SEHL01": "Clocks, lamps, and decorator items",
+            "SEHL02": "Indoor plants and flowers",
+            "SEHL03": "Dishes and flatware",
+            "SEHL04": "Nonelectric cookware and tableware",
+            "SEHM": "Tools, hardware, outdoor equipment and supplies",
+            "SEHM01": "Tools, hardware and supplies",
+            "SEHM02": "Outdoor equipment and supplies",
+            "SEHN": "Housekeeping supplies",
+            "SEHN01": "Household cleaning products",
+            "SEHN02": "Household paper products",
+            "SEHN03": "Miscellaneous household products",
+            "SEHP": "Household operations",
+            "SEHP01": "Domestic services",
+            "SEHP02": "Gardening and lawncare services",
+            "SEHP03": "Moving, storage, freight expense",
+            "SEHP04": "Repair of household items",
+            "SEMC": "Professional services",
+            "SEMC01": "Physicians' services",
+            "SEMC02": "Dental services",
+            "SEMC03": "Eyeglasses and eye care",
+            "SEMC04": "Services by other medical professionals",
+            "SEMD": "Hospital and related services",
+            "SEMD01": "Hospital services",
+            "SEMD02": "Nursing homes and adult day services",
+            "SEMD03": "Care of invalids and elderly at home",
+            "SEME": "Health insurance",
+            "SEMF": "Medicinal drugs",
+            "SEMF01": "Prescription drugs",
+            "SEMF02": "Nonprescription drugs",
+            "SEMG": "Medical equipment and supplies",
+            "SERA": "Video and audio",
+            "SERA01": "Televisions",
+            "SERA02": "Cable, satellite, and live streaming television service",
+            "SERA03": "Other video equipment",
+            "SERA04": "Purchase, subscription, and rental of video",
+            "SERA05": "Audio equipment",
+            "SERA06": "Recorded music and music subscriptions",
+            "SERAC": "Video and audio products",
+            "SERAS": "Video and audio services",
+            "SERB": "Pets, pet products and services",
+            "SERB01": "Pets and pet products",
+            "SERB02": "Pet services including veterinary",
+            "SERC": "Sporting goods",
+            "SERC01": "Sports vehicles including bicycles",
+            "SERC02": "Sports equipment",
+            "SERD": "Photography",
+            "SERD01": "Photographic equipment and supplies",
+            "SERD02": "Photographers and photo processing",
+            "SERE": "Other recreational goods",
+            "SERE01": "Toys",
+            "SERE02": "Sewing machines, fabric and supplies",
+            "SERE03": "Music instruments and accessories",
+            "SERF": "Other recreation services",
+            "SERF01": "Club membership for shopping clubs, fraternal, or other organizations, or participant sports fees",
+            "SERF02": "Admissions",
+            "SERF03": "Fees for lessons or instructions",
+            "SERG": "Recreational reading materials",
+            "SERG01": "Newspapers and magazines",
+            "SERG02": "Recreational books",
+            "SETA": "New and used motor vehicles",
+            "SETA01": "New vehicles",
+            "SETA02": "Used cars and trucks",
+            "SETA03": "Leased cars and trucks",
+            "SETA04": "Car and truck rental",
+            "SETB": "Motor fuel",
+            "SETB01": "Gasoline (all types)",
+            "SETB02": "Other motor fuels",
+            "SETC": "Motor vehicle parts and equipment",
+            "SETC01": "Tires",
+            "SETC02": "Vehicle accessories other than tires",
+            "SETD": "Motor vehicle maintenance and repair",
+            "SETD01": "Motor vehicle body work",
+            "SETD02": "Motor vehicle maintenance and servicing",
+            "SETD03": "Motor vehicle repair",
+            "SETE": "Motor vehicle insurance",
+            "SETF": "Motor vehicle fees",
+            "SETF01": "State motor vehicle registration and license fees",
+            "SETF03": "Parking and other fees",
+            "SETG": "Public transportation",
+            "SETG01": "Airline fares",
+            "SETG02": "Other intercity transportation",
+            "SETG03": "Intracity transportation",
+            "SS47014": "Gasoline, unleaded regular",
+            "SS47015": "Gasoline, unleaded midgrade",
+            "SS47016": "Gasoline, unleaded premium",
+            "SS5702": "Inpatient hospital services",
+            "SS5703": "Outpatient hospital services"
+        },
+        "base_code": {
+            "A": "Alternate",
+            "S": "Current"
+        }
+    },
+    "li": {
+        "area_code": {
+            "0000": "U.S. city average"
+        },
+        "item_code": {
+            "SL00001": "Piece goods",
+            "SL00002": "Domestics and draperies",
+            "SL00003": "Women's and children's shoes",
+            "SL00004": "Men's shoes",
+            "SL00005": "Infants' wear and furniture",
+            "SL00006": "Women's underwear",
+            "SL00007": "Women's and girls' hosiery",
+            "SL00008": "Women's and girls' accessories",
+            "SL00009": "Women's outerwear & girls' wear",
+            "SL00010": "Men's clothing",
+            "SL00011": "Men's furnishings",
+            "SL00012": "Boys' wear",
+            "SL00013": "Jewelry and silverware",
+            "SL00014": "Notions",
+            "SL00015": "Toilet articles & drugs",
+            "SL00016": "Furniture and bedding",
+            "SL00017": "Floor coverings",
+            "SL00018": "Housewares",
+            "SL00019": "Major appliances",
+            "SL00020": "Radios and television sets",
+            "SL00021": "Recreation & education",
+            "SL00022": "Home improvements",
+            "SL00023": "Automotive accessories",
+            "SLDUR": "Durable goods",
+            "SLMISC": "Miscellaneous",
+            "SLSOFT": "Soft goods",
+            "SLTOTAL": "Store total"
+        }
+    },
+    "su": {
+        "area_code": {
+            "0000": "U.S. city average"
+        },
+        "item_code": {
+            "SA0": "All items",
+            "SA0E": "Energy",
+            "SA0L1E": "All items less food and energy",
+            "SAA": "Apparel",
+            "SAC": "Commodities",
+            "SAD": "Durables",
+            "SAE": "Education and communication",
+            "SAE1": "Education",
+            "SAE2": "Communication",
+            "SAF": "Food and beverages",
+            "SAF1": "Food",
+            "SAF11": "Food at home",
+            "SAF116": "Alcoholic beverages",
+            "SAG": "Other goods and services",
+            "SAH": "Housing",
+            "SAH1": "Shelter",
+            "SAH2": "Fuels and utilities",
+            "SAH3": "Household furnishings and operations",
+            "SAM": "Medical care",
+            "SAM1": "Medical care commodities",
+            "SAM2": "Medical care services",
+            "SAN": "Nondurables",
+            "SAR": "Recreation",
+            "SAS": "Services",
+            "SAT": "Transportation",
+            "SAT1": "Private transportation",
+            "SEFV": "Food away from home",
+            "SETA01": "New vehicles",
+            "SETG": "Public transportation"
+        },
+        "base_code": {
+            "S": "Current"
+        },
+        "footnote_code": {
+            "I": "Initial",
+            "U": "Interim"
+        }
+    },
+    "ei": {
+        "index_code": {
+            "CD": "Locality of Destination Price Indexes",
+            "CO": "Locality of Origin Price Indexes",
+            "CT": "Terms of Trade Indexes",
+            "IC": "Services Inbound Price Indexes",
+            "ID": "Harmonized System Export Price Indexes",
+            "IH": "Services Export Price Indexes",
+            "IP": "Harmonized System Import Price Indexes",
+            "IQ": "BEA End Use Export Price Indexes",
+            "IR": "BEA End Use Import Price Indexes",
+            "IS": "Services Outbound Price Indexes",
+            "IV": "Services Import Price Indexes",
+            "IY": "NAICS Export Price Indexes",
+            "IZ": "NAICS Import Price Indexes"
+        },
+        "footnote_code": {
+            "2": "Western Europe, Canada, Japan, Australia, New Zealand, and South Africa.",
+            "3": "Mexico, Central America, South America, and the Caribbean.",
+            "4": "China, Japan, Australia, Brunei, Indonesia, Macao, Malaysia, New Zealand, Papua New Guinea, Philippines, and the Asian Newly Industrialized Countries.",
+            "5": "Asian Newly Industrialized Countries - Hong Kong, Singapore, South Korea, and Taiwan.",
+            "6": "Association of Southeast Asian Nations - Brunei, Cambodia, Indonesia, Laos, Malaysia, Myanmar, Philippines, Singapore, Thailand, and Vietnam.",
+            "7": "Bahrain, Iran, Iraq, Israel, Jordan, Kuwait, Lebanon, Oman, Qatar, Saudi Arabia, Syria, United Arab Emirates, and Yemen.",
+            "R": "Revised."
+        }
+    }
+}

openbb_platform/providers/bls/openbb_bls/assets/cpi_series.xz

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0ecda2eabd75029d0979419168822c4ef48b4841e7d712c44ebada67e09836e5
+size 106780

openbb_platform/providers/bls/openbb_bls/assets/cps_codes.json

@@ -0,0 +1,1155 @@
+{
+    "le": {
+        "lfst_code": {
+            "20": "Employed",
+            "25": "Employed full time",
+            "26": "Employed part time"
+        },
+        "fips_code": {
+            "00": "U.S. Total",
+            "01": "Alabama",
+            "02": "Alaska",
+            "04": "Arizona",
+            "05": "Arkansas",
+            "06": "California",
+            "08": "Colorado",
+            "09": "Connecticut",
+            "10": "Delaware",
+            "11": "District of Columbia",
+            "12": "Florida",
+            "13": "Georgia",
+            "15": "Hawaii",
+            "16": "Idaho",
+            "17": "Illinois",
+            "18": "Indiana",
+            "19": "Iowa",
+            "20": "Kansas",
+            "21": "Kentucky",
+            "22": "Louisiana",
+            "23": "Maine",
+            "24": "Maryland",
+            "25": "Massachusetts",
+            "26": "Michigan",
+            "27": "Minnesota",
+            "28": "Mississippi",
+            "29": "Missouri",
+            "30": "Montana",
+            "31": "Nebraska",
+            "32": "Nevada",
+            "33": "New Hampshire",
+            "34": "New Jersey",
+            "35": "New Mexico",
+            "36": "New York",
+            "37": "North Carolina",
+            "38": "North Dakota",
+            "39": "Ohio",
+            "40": "Oklahoma",
+            "41": "Oregon",
+            "42": "Pennsylvania",
+            "44": "Rhode Island",
+            "45": "South Carolina",
+            "46": "South Dakota",
+            "47": "Tennessee",
+            "48": "Texas",
+            "49": "Utah",
+            "50": "Vermont",
+            "51": "Virginia",
+            "53": "Washington",
+            "54": "West Virginia",
+            "55": "Wisconsin",
+            "56": "Wyoming",
+            "81": "New England",
+            "82": "Middle Atlantic",
+            "83": "East North Central",
+            "84": "West North Central",
+            "85": "South Atlantic",
+            "86": "East South Central",
+            "87": "West South Central",
+            "88": "Mountain",
+            "89": "Pacific",
+            "91": "Northeast",
+            "92": "Midwest",
+            "93": "South",
+            "94": "West"
+        },
+        "tdata_code": {
+            "00": "Number in thousands",
+            "01": "Percent or rate"
+        },
+        "pcts_code": {
+            "00": null,
+            "05": "Percent distribution of hourly paid workers",
+            "22": "Percent of hourly paid workers",
+            "49": "EARNINGS OF FOREIGN BORN AS PERCENT OF NATIVE BORN",
+            "50": "Earnings of women as a percent of men",
+            "99": "100% place holder"
+        },
+        "earn_code": {
+            "00": "Person counts (number in thousands)",
+            "01": "Median usual weekly earnings - in current dollars (second quartile)",
+            "02": "Median usual weekly earnings - in constant (1982-84) dollars",
+            "03": "Usual weekly earnings - in current dollars (first decile)",
+            "04": "Usual weekly earnings - in current dollars (first quartile)",
+            "05": "Usual weekly earnings - in current dollars (third quartile)",
+            "06": "Usual weekly earnings - in current dollars (ninth decile)",
+            "07": "Workers paid hourly rates",
+            "08": "Below prevailing federal minimum wage",
+            "09": "At prevailing federal minimum wage",
+            "10": "Total at or below prevailing federal minimum wage",
+            "11": "Median Hourly Earnings - in current dollars",
+            "13": "Median usual weekly earnings - in constant (base current year) dollars",
+            "14": "Median hourly earnings - in constant (base current year) dollars"
+        },
+        "cert_code": {
+            "00": null,
+            "01": "Without a certification or license",
+            "02": "With a certification or license",
+            "03": "With a certification, but no license",
+            "04": "With a license"
+        },
+        "class_code": {
+            "03": "Government wage and salary workers",
+            "04": "Federal wage and salary workers",
+            "05": "State wage and salary workers",
+            "06": "Local wage and salary workers",
+            "16": "Wage and salary workers, excluding incorporated self employed",
+            "17": "Private wage and salary workers, excluding incorporated self employed"
+        },
+        "unin_code": {
+            "0": null,
+            "1": "MEMBERS OF UNIONS",
+            "2": "REPRESENTED BY UNIONS",
+            "3": "NON-UNION"
+        },
+        "indy_code": {
+            "0000": "All Industries",
+            "0168": "Agriculture and related industries",
+            "0368": "Nonagriculture industries",
+            "0369": "Mining, quarrying, and oil and gas extraction",
+            "0569": "Utilities",
+            "0770": "Construction",
+            "1068": "Nondurable goods manufacturing",
+            "2467": "Manufacturing",
+            "2468": "Durable goods manufacturing",
+            "4067": "Wholesale and retail trade",
+            "4068": "Wholesale trade",
+            "4669": "Retail trade",
+            "6068": "Transportation and utilities",
+            "6069": "Transportation and warehousing",
+            "6468": "Information",
+            "6469": "Publishing, except Internet",
+            "6569": "Motion pictures and sound recording industries",
+            "6670": "Radio and television broadcasting and cable subscriptions programming",
+            "6679": "Telecommunications",
+            "6769": "Other information services",
+            "6867": "Financial activities",
+            "6868": "Finance and insurance",
+            "6869": "Finance",
+            "6990": "Insurance carriers and related activities",
+            "7069": "Real estate and rental and leasing",
+            "7268": "Professional and business services",
+            "7269": "Professional and technical services",
+            "7569": "Management, administrative, and waste services",
+            "7858": "Education and health services",
+            "7859": "Educational services",
+            "7968": "Health care and social assistance",
+            "8558": "Leisure and hospitality",
+            "8559": "Arts, entertainment, and recreation",
+            "8658": "Accommodation and food services",
+            "8659": "Accommodation",
+            "8679": "Food services and drinking places",
+            "8767": "Other services",
+            "8768": "Other services, except private households",
+            "9290": "Other services, private households"
+        },
+        "occupation_code": {
+            "0000": "All Occupations",
+            "0007": "Management, professional and related occupations",
+            "0008": "Management, business, and financial operations occupations",
+            "0009": "Management occupations",
+            "0010": "Chief executives",
+            "0020": "General and operations managers",
+            "0030": "Legislators",
+            "0040": "Advertising and promotions managers",
+            "0050": "Marketing and Sales Managers",
+            "0051": "Marketing managers",
+            "0052": "Sales managers",
+            "0060": "Public relations and fundraising managers",
+            "0100": "Administrative Services Managers",
+            "0101": "Administrative services managers",
+            "0102": "Facilities managers",
+            "0110": "Computer and information systems managers",
+            "0120": "Financial managers",
+            "0135": "Compensation and benefits managers",
+            "0136": "Human resources managers",
+            "0137": "Training and development managers",
+            "0140": "Industrial production managers",
+            "0150": "Purchasing managers",
+            "0160": "Transportation, storage, and distribution managers",
+            "0200": "Farm, Ranch, and Other Agricultural Managers",
+            "0205": "Farmers, ranchers, and other agricultural managers",
+            "0220": "Construction managers",
+            "0230": "Education and childcare administrators",
+            "0300": "Architectural and engineering managers",
+            "0310": "Food service managers",
+            "0325": "Funeral home managers",
+            "0335": "Entertainment and recreation managers",
+            "0340": "Lodging managers",
+            "0350": "Medical and health services managers",
+            "0360": "Natural sciences managers",
+            "0400": "Postmasters and mail superintendents",
+            "0410": "Property, real estate, and community association managers",
+            "0420": "Social and community service managers",
+            "0425": "Emergency management directors",
+            "0426": "Personal service managers, all other",
+            "0430": "Managers, All Other",
+            "0440": "Managers, all other",
+            "0499": "Business and financial operations occupations",
+            "0500": "Agents and business managers of artists, performers, and athletes",
+            "0510": "Buyers and purchasing agents, farm products",
+            "0520": "Wholesale and retail buyers, except farm products",
+            "0530": "Purchasing agents, except wholesale, retail, and farm products",
+            "0540": "Claims adjusters, appraisers, examiners, and investigators",
+            "0560": "Compliance Officers, Except Agriculture, Construction, Health and Safety, and Transportation",
+            "0565": "Compliance officers",
+            "0600": "Cost estimators",
+            "0620": "Human Resources, Training, and Labor Relations Specialists",
+            "0630": "Human resources workers",
+            "0640": "Compensation, benefits, and job analysis specialists",
+            "0650": "Training and development specialists",
+            "0700": "Logisticians",
+            "0705": "Project management specialists",
+            "0710": "Management analysts",
+            "0725": "Meeting, convention, and event planners",
+            "0726": "Fundraisers",
+            "0735": "Market research analysts and marketing specialists",
+            "0740": "Business Operations Specialists, All Other",
+            "0750": "Business operations specialists, all other",
+            "0800": "Accountants and auditors",
+            "0810": "Property appraisers and assessors",
+            "0820": "Budget analysts",
+            "0830": "Credit analysts",
+            "0840": "Financial Analysts",
+            "0845": "Financial and investment analysts",
+            "0850": "Personal financial advisors",
+            "0860": "Insurance underwriters",
+            "0900": "Financial examiners",
+            "0910": "Credit counselors and loan officers",
+            "0930": "Tax examiners and collectors, and revenue agents",
+            "0940": "Tax preparers",
+            "0960": "Other financial specialists",
+            "0998": "Professional and related occupations",
+            "0999": "Computer and mathematical occupations",
+            "1000": "Computer Scientists and Systems Analysts",
+            "1005": "Computer and information research scientists",
+            "1006": "Computer systems analysts",
+            "1007": "Information security analysts",
+            "1010": "Computer programmers",
+            "1020": "Software Developers, Applications and Systems Software",
+            "1021": "Software developers",
+            "1022": "Software quality assurance analysts and testers",
+            "1030": "Web Developers",
+            "1031": "Web developers",
+            "1032": "Web or digital interface designers",
+            "1050": "Computer support specialists",
+            "1065": "Database administrators and architects",
+            "1105": "Network and computer systems administrators",
+            "1106": "Computer network architects",
+            "1107": "Computer Occupations, All Other",
+            "1108": "Computer occupations, all other",
+            "1110": "Network Systems and Data Communications Analysts",
+            "1200": "Actuaries",
+            "1210": "Mathematicians",
+            "1220": "Operations research analysts",
+            "1230": "Statisticians",
+            "1240": "Other mathematical science occupations",
+            "1299": "Architecture and engineering occupations",
+            "1300": "Architects, Except Naval",
+            "1305": "Architects, except landscape and naval",
+            "1306": "Landscape architects",
+            "1310": "Surveyors, cartographers, and photogrammetrists",
+            "1320": "Aerospace engineers",
+            "1330": "Agricultural engineers",
+            "1340": "Biomedical engineers",
+            "1350": "Chemical engineers",
+            "1360": "Civil engineers",
+            "1400": "Computer hardware engineers",
+            "1410": "Electrical and electronics engineers",
+            "1420": "Environmental engineers",
+            "1430": "Industrial engineers, including health and safety",
+            "1440": "Marine engineers and naval architects",
+            "1450": "Materials engineers",
+            "1460": "Mechanical engineers",
+            "1500": "Mining and geological engineers, including mining safety engineers",
+            "1510": "Nuclear engineers",
+            "1520": "Petroleum engineers",
+            "1530": "Engineers, all other",
+            "1540": "Drafters",
+            "1541": "Architectural and civil drafters",
+            "1545": "Other drafters",
+            "1550": "Engineering Technicians, Except Drafters",
+            "1551": "Electrical and electronic engineering technologists and technicians",
+            "1555": "Other engineering technologists and technicians, except drafters",
+            "1560": "Surveying and mapping technicians",
+            "1599": "Life, physical, and social science occupations",
+            "1600": "Agricultural and food scientists",
+            "1610": "Biological scientists",
+            "1640": "Conservation scientists and foresters",
+            "1650": "Medical scientists",
+            "1660": "Life scientists, all other",
+            "1700": "Astronomers and physicists",
+            "1710": "Atmospheric and space scientists",
+            "1720": "Chemists and materials scientists",
+            "1740": "Environmental Scientists and Geoscientists",
+            "1745": "Environmental scientists and specialists, including health",
+            "1750": "Geoscientists and hydrologists, except geographers",
+            "1760": "Physical scientists, all other",
+            "1800": "Economists",
+            "1810": "Market and Survey Researchers",
+            "1815": "Survey researchers",
+            "1820": "Psychologists",
+            "1821": "Clinical and counseling psychologists",
+            "1822": "School psychologists",
+            "1825": "Other psychologists",
+            "1830": "Sociologists",
+            "1840": "Urban and regional planners",
+            "1860": "Miscellaneous social scientists and related workers",
+            "1900": "Agricultural and food science technicians",
+            "1910": "Biological technicians",
+            "1920": "Chemical technicians",
+            "1935": "Geoscience and environmental science technicians",
+            "1940": "Nuclear technicians",
+            "1950": "Social science research assistants",
+            "1965": "Miscellaneous Life, Physical, and Social Science Technicians",
+            "1970": "Other life, physical, and social science technicians",
+            "1980": "Occupational health and safety specialists and technicians",
+            "1999": "Community and social service occupations",
+            "2000": "Counselors",
+            "2001": "Substance abuse and behavioral disorder counselors",
+            "2002": "Educational, guidance, and career counselors and advisors",
+            "2003": "Marriage and family therapists",
+            "2004": "Mental health counselors",
+            "2005": "Rehabilitation counselors",
+            "2006": "Counselors, all other",
+            "2010": "Social Workers",
+            "2011": "Child, family, and school social workers",
+            "2012": "Healthcare social workers",
+            "2013": "Mental health and substance abuse social workers",
+            "2014": "Social workers, all other",
+            "2015": "Probation officers and correctional treatment specialists",
+            "2016": "Social and human service assistants",
+            "2020": "Miscellaneous Community and Social Service Specialists",
+            "2025": "Other community and social service specialists",
+            "2040": "Clergy",
+            "2050": "Directors, religious activities and education",
+            "2060": "Religious workers, all other",
+            "2099": "Legal occupations",
+            "2100": "Lawyers",
+            "2105": "Judicial law clerks",
+            "2110": "Judges, magistrates, and other judicial workers",
+            "2145": "Paralegals and legal assistants",
+            "2160": "Miscellaneous Legal Support Workers",
+            "2170": "Title examiners, abstractors, and searchers",
+            "2180": "Legal support workers, all other",
+            "2199": "Education, training, and library occupations",
+            "2200": "Postsecondary Teachers",
+            "2205": "Postsecondary teachers",
+            "2300": "Preschool and kindergarten teachers",
+            "2310": "Elementary and middle school teachers",
+            "2320": "Secondary school teachers",
+            "2330": "Special education teachers",
+            "2340": "Other Teachers and Instructors",
+            "2350": "Tutors",
+            "2360": "Other teachers and instructors",
+            "2400": "Archivists, curators, and museum technicians",
+            "2435": "Librarians and media collections specialists",
+            "2440": "Library technicians",
+            "2545": "Teacher assistants",
+            "2550": "Other Education, Training, and Library Workers",
+            "2555": "Other educational instruction and library workers",
+            "2599": "Arts, design, entertainment, sports, and media occupations",
+            "2600": "Artists and related workers",
+            "2630": "Designers",
+            "2631": "Commercial and industrial designers",
+            "2632": "Fashion designers",
+            "2633": "Floral designers",
+            "2634": "Graphic designers",
+            "2635": "Interior designers",
+            "2636": "Merchandise displayers and window trimmers",
+            "2640": "Other designers",
+            "2700": "Actors",
+            "2710": "Producers and directors",
+            "2720": "Athletes, Coaches, Umpires, and Related Workers",
+            "2721": "Athletes and sports competitors",
+            "2722": "Coaches and scouts",
+            "2723": "Umpires, referees, and other sports officials",
+            "2740": "Dancers and choreographers",
+            "2750": "Musicians, Singers, and Related Workers",
+            "2751": "Music directors and composers",
+            "2752": "Musicians and singers",
+            "2755": "Disc jockeys, except radio disc jockeys",
+            "2760": "Entertainers and Performers, Sports and Related Workers, All Other",
+            "2770": "Entertainers and performers, sports and related workers, all other",
+            "2800": "Announcers",
+            "2805": "Broadcast announcers and radio disc jockeys",
+            "2810": "News analysts, reporters, and journalists",
+            "2825": "Public relations specialists",
+            "2830": "Editors",
+            "2840": "Technical writers",
+            "2850": "Writers and authors",
+            "2860": "Miscellaneous Media and Communication Workers",
+            "2861": "Interpreters and translators",
+            "2862": "Court reporters and simultaneous captioners",
+            "2865": "Media and communication workers, all other",
+            "2900": "Broadcast and Sound Engineering Technicians and Radio Operators",
+            "2905": "Broadcast, sound, and lighting technicians",
+            "2910": "Photographers",
+            "2920": "Television, video, and film camera operators and editors",
+            "2960": "Media and Communication Equipment Workers, All Other",
+            "2970": "Media and communication equipment workers, all other",
+            "2999": "Healthcare practitioners and technical occupations",
+            "3000": "Chiropractors",
+            "3010": "Dentists",
+            "3030": "Dietitians and nutritionists",
+            "3040": "Optometrists",
+            "3050": "Pharmacists",
+            "3060": "Physicians and Surgeons",
+            "3065": "Emergency medicine physicians",
+            "3070": "Radiologists",
+            "3090": "Other physicians",
+            "3100": "Surgeons",
+            "3110": "Physician assistants",
+            "3120": "Podiatrists",
+            "3140": "Audiologists",
+            "3150": "Occupational therapists",
+            "3160": "Physical therapists",
+            "3200": "Radiation therapists",
+            "3210": "Recreational therapists",
+            "3220": "Respiratory therapists",
+            "3230": "Speech-language pathologists",
+            "3235": "Exercise physiologists",
+            "3245": "Therapists, all other",
+            "3250": "Veterinarians",
+            "3255": "Registered nurses",
+            "3256": "Nurse anesthetists",
+            "3257": "Nurse midwives",
+            "3258": "Nurse practitioners",
+            "3260": "Health Diagnosing and Treating Practitioners, All Other",
+            "3261": "Acupuncturists",
+            "3270": "Healthcare diagnosing or treating practitioners, all other",
+            "3300": "Clinical laboratory technologists and technicians",
+            "3310": "Dental hygienists",
+            "3320": "Diagnostic Related Technologists and Technicians",
+            "3321": "Cardiovascular technologists and technicians",
+            "3322": "Diagnostic medical sonographers",
+            "3323": "Radiologic technologists and technicians",
+            "3324": "Magnetic resonance imaging technologists",
+            "3330": "Nuclear medicine technologists and medical dosimetrists",
+            "3400": "Emergency Medical Technicians and Paramedics",
+            "3401": "Emergency medical technicians",
+            "3402": "Paramedics",
+            "3410": "Health Diagnosing and Treating Practitioner Support Technicians",
+            "3420": "Health Practitioner Support Technologists and Technicians",
+            "3421": "Pharmacy technicians",
+            "3422": "Psychiatric technicians",
+            "3423": "Surgical technologists",
+            "3424": "Veterinary technologists and technicians",
+            "3430": "Dietetic technicians and ophthalmic medical technicians",
+            "3500": "Licensed practical and licensed vocational nurses",
+            "3510": "Medical Records and Health Information Technicians",
+            "3515": "Medical records specialists",
+            "3520": "Opticians, dispensing",
+            "3540": "Other Healthcare Practitioners and Technical Occupations",
+            "3545": "Miscellaneous health technologists and technicians",
+            "3550": "Other healthcare practitioners and technical occupations",
+            "3597": "Service occupations",
+            "3599": "Healthcare support occupations",
+            "3600": "Nursing, Psychiatric, and Home Health Aides",
+            "3601": "Home health aides",
+            "3602": "Personal care aides",
+            "3603": "Nursing assistants",
+            "3605": "Orderlies and psychiatric aides",
+            "3610": "Occupational therapy assistants and aides",
+            "3620": "Physical therapist assistants and aides",
+            "3630": "Massage therapists",
+            "3640": "Dental assistants",
+            "3645": "Medical assistants",
+            "3646": "Medical transcriptionists",
+            "3647": "Pharmacy aides",
+            "3648": "Veterinary assistants and laboratory animal caretakers",
+            "3649": "Phlebotomists",
+            "3655": "Other healthcare support workers",
+            "3699": "Protective service occupations",
+            "3700": "First-line supervisors of correctional officers",
+            "3710": "First-line supervisors of police and detectives",
+            "3720": "First-line supervisors of fire fighting and prevention workers",
+            "3725": "First-line supervisors of security workers",
+            "3730": "First-Line Supervisors of Protective Service Workers, All Other",
+            "3735": "First-line supervisors of protective service workers, all other",
+            "3740": "Firefighters",
+            "3750": "Fire inspectors",
+            "3800": "Bailiffs, Correctional Officers, and Jailers",
+            "3801": "Bailiffs",
+            "3802": "Correctional officers and jailers",
+            "3820": "Detectives and criminal investigators",
+            "3830": "Fish and game wardens",
+            "3840": "Parking enforcement workers",
+            "3850": "Police and Sheriff's Patrol Officers",
+            "3860": "Transit and Railroad Police",
+            "3870": "Police officers",
+            "3900": "Animal control workers",
+            "3910": "Private detectives and investigators",
+            "3930": "Security guards and gaming surveillance officers",
+            "3940": "Crossing guards and flaggers",
+            "3945": "Transportation security screeners",
+            "3946": "School bus monitors",
+            "3955": "Lifeguards and Other Recreational, and All Other Protective Service Workers",
+            "3960": "Other protective service workers",
+            "3999": "Food preparation and serving related occupations",
+            "4000": "Chefs and head cooks",
+            "4010": "First-line supervisors of food preparation and serving workers",
+            "4020": "Cooks",
+            "4030": "Food preparation workers",
+            "4040": "Bartenders",
+            "4050": "Combined Food Preparation and Serving Workers, Including Fast Food",
+            "4055": "Fast food and counter workers",
+            "4060": "Counter Attendants, Cafeteria, Food Concession, and Coffee Shop",
+            "4110": "Waiters and waitresses",
+            "4120": "Food servers, nonrestaurant",
+            "4130": "Dining room and cafeteria attendants and bartender helpers",
+            "4140": "Dishwashers",
+            "4150": "Hosts and hostesses, restaurant, lounge, and coffee shop",
+            "4160": "Food preparation and serving related workers, all other",
+            "4199": "Building and grounds cleaning and maintenance occupations",
+            "4200": "First-line supervisors of housekeeping and janitorial workers",
+            "4210": "First-line supervisors of landscaping, lawn service, and groundskeeping workers",
+            "4220": "Janitors and building cleaners",
+            "4230": "Maids and housekeeping cleaners",
+            "4240": "Pest control workers",
+            "4250": "Grounds Maintenance Workers",
+            "4251": "Landscaping and groundskeeping workers",
+            "4252": "Tree trimmers and pruners",
+            "4255": "Other grounds maintenance workers",
+            "4299": "Personal care and service occupations",
+            "4300": "First-Line Supervisors of Gaming Workers",
+            "4320": "First-Line Supervisors of Personal Service Workers",
+            "4330": "Supervisors of personal care and service workers",
+            "4340": "Animal trainers",
+            "4350": "Animal caretakers",
+            "4400": "Gambling services workers",
+            "4410": "Motion Picture Projectionists",
+            "4420": "Ushers, lobby attendants, and ticket takers",
+            "4430": "Miscellaneous Entertainment Attendants and Related Workers",
+            "4435": "Other entertainment attendants and related workers",
+            "4461": "Embalmers, crematory operators and funeral attendants",
+            "4465": "Morticians, undertakers, and funeral arrangers",
+            "4500": "Barbers",
+            "4510": "Hairdressers, hairstylists, and cosmetologists",
+            "4520": "Miscellaneous Personal Appearance Workers",
+            "4521": "Manicurists and pedicurists",
+            "4522": "Skincare specialists",
+            "4525": "Other personal appearance workers",
+            "4530": "Baggage porters, bellhops, and concierges",
+            "4540": "Tour and travel guides",
+            "4550": "Transportation Attendants",
+            "4600": "Childcare workers",
+            "4620": "Recreation and Fitness Workers",
+            "4621": "Exercise trainers and group fitness instructors",
+            "4622": "Recreation workers",
+            "4640": "Residential advisors",
+            "4650": "Personal Care and Service Workers, All Other",
+            "4655": "Personal care and service workers, all other",
+            "4698": "Sales and office occupations",
+            "4699": "Sales and related occupations",
+            "4700": "First-line supervisors of retail sales workers",
+            "4710": "First-line supervisors of non-retail sales workers",
+            "4720": "Cashiers",
+            "4740": "Counter and rental clerks",
+            "4750": "Parts salespersons",
+            "4760": "Retail salespersons",
+            "4800": "Advertising sales agents",
+            "4810": "Insurance sales agents",
+            "4820": "Securities, commodities, and financial services sales agents",
+            "4830": "Travel agents",
+            "4840": "Sales representatives of services, except advertising, insurance, travel, and financial services",
+            "4850": "Sales representatives, wholesale and manufacturing",
+            "4900": "Models, demonstrators, and product promoters",
+            "4920": "Real estate brokers and sales agents",
+            "4930": "Sales engineers",
+            "4940": "Telemarketers",
+            "4950": "Door-to-door sales workers, news and street vendors, and related workers",
+            "4965": "Sales and related workers, all other",
+            "4999": "Office and administrative support occupations",
+            "5000": "First-line supervisors of office and administrative support workers",
+            "5010": "Switchboard operators, including answering service",
+            "5020": "Telephone operators",
+            "5040": "Communications equipment operators, all other",
+            "5100": "Bill and account collectors",
+            "5110": "Billing and posting clerks",
+            "5120": "Bookkeeping, accounting, and auditing clerks",
+            "5130": "Gambling cage workers",
+            "5140": "Payroll and timekeeping clerks",
+            "5150": "Procurement clerks",
+            "5160": "Tellers",
+            "5165": "Financial clerks, all other",
+            "5200": "Brokerage clerks",
+            "5210": "Correspondence clerks",
+            "5220": "Court, municipal, and license clerks",
+            "5230": "Credit authorizers, checkers, and clerks",
+            "5240": "Customer service representatives",
+            "5250": "Eligibility interviewers, government programs",
+            "5260": "File Clerks",
+            "5300": "Hotel, motel, and resort desk clerks",
+            "5310": "Interviewers, except eligibility and loan",
+            "5320": "Library assistants, clerical",
+            "5330": "Loan interviewers and clerks",
+            "5340": "New accounts clerks",
+            "5350": "Order clerks",
+            "5360": "Human resources assistants, except payroll and timekeeping",
+            "5400": "Receptionists and information clerks",
+            "5410": "Reservation and transportation ticket agents and travel clerks",
+            "5420": "Information and record clerks, all other",
+            "5500": "Cargo and freight agents",
+            "5510": "Couriers and messengers",
+            "5520": "Dispatchers",
+            "5521": "Public safety telecommunicators",
+            "5522": "Dispatchers, except police, fire, and ambulance",
+            "5530": "Meter readers, utilities",
+            "5540": "Postal service clerks",
+            "5550": "Postal service mail carriers",
+            "5560": "Postal service mail sorters, processors, and processing machine operators",
+            "5600": "Production, planning, and expediting clerks",
+            "5610": "Shipping, receiving, and inventory clerks",
+            "5630": "Weighers, measurers, checkers, and samplers, recordkeeping",
+            "5700": "Secretaries and Administrative Assistants",
+            "5710": "Executive secretaries and executive administrative assistants",
+            "5720": "Legal secretaries and administrative assistants",
+            "5730": "Medical secretaries and administrative assistants",
+            "5740": "Secretaries and administrative assistants, except legal, medical, and executive",
+            "5810": "Data entry keyers",
+            "5820": "Word processors and typists",
+            "5830": "Desktop publishers",
+            "5840": "Insurance claims and policy processing clerks",
+            "5850": "Mail clerks and mail machine operators, except postal service",
+            "5860": "Office clerks, general",
+            "5900": "Office machine operators, except computer",
+            "5910": "Proofreaders and copy markers",
+            "5920": "Statistical assistants",
+            "5940": "Office and administrative support workers, all other",
+            "5998": "Natural resources, construction, and maintenance occupations",
+            "5999": "Farming, fishing, and forestry occupations",
+            "6005": "First-line supervisors of farming, fishing, and forestry workers",
+            "6010": "Agricultural inspectors",
+            "6020": "Animal breeders",
+            "6040": "Graders and sorters, agricultural products",
+            "6050": "Miscellaneous agricultural workers",
+            "6100": "Fishers and Related Fishing Workers",
+            "6110": "Hunters and Trappers",
+            "6115": "Fishing and hunting workers",
+            "6120": "Forest and conservation workers",
+            "6130": "Logging workers",
+            "6199": "Construction and extraction occupations",
+            "6200": "First-line supervisors of construction trades and extraction workers",
+            "6210": "Boilermakers",
+            "6220": "Brickmasons, blockmasons, and stonemasons",
+            "6230": "Carpenters",
+            "6240": "Carpet, floor, and tile installers and finishers",
+            "6250": "Cement masons, concrete finishers, and terrazzo workers",
+            "6260": "Construction laborers",
+            "6300": "Paving, Surfacing, and Tamping Equipment Operators",
+            "6305": "Construction equipment operators",
+            "6310": "Pile-Driver Operators",
+            "6320": "Operating Engineers and Other Construction Equipment Operators",
+            "6330": "Drywall installers, ceiling tile installers, and tapers",
+            "6355": "Electricians",
+            "6360": "Glaziers",
+            "6400": "Insulation workers",
+            "6410": "Painters and paperhangers",
+            "6420": "Painters, Construction and Maintenance",
+            "6430": "Paperhangers",
+            "6440": "Pipelayers, Plumbers, Pipefitters, and Steamfitters",
+            "6441": "Pipelayers",
+            "6442": "Plumbers, pipefitters, and steamfitters",
+            "6460": "Plasterers and stucco masons",
+            "6500": "Reinforcing iron and rebar workers",
+            "6515": "Roofers",
+            "6520": "Sheet metal workers",
+            "6530": "Structural iron and steel workers",
+            "6540": "Solar photovoltaic installers",
+            "6600": "Helpers, construction trades",
+            "6660": "Construction and building inspectors",
+            "6700": "Elevator installers and repairers",
+            "6710": "Fence erectors",
+            "6720": "Hazardous materials removal workers",
+            "6730": "Highway maintenance workers",
+            "6740": "Rail-track laying and maintenance equipment operators",
+            "6750": "Septic tank servicers and sewer pipe cleaners",
+            "6765": "Miscellaneous construction and related workers",
+            "6800": "Derrick, rotary drill, and service unit operators, oil and gas",
+            "6820": "Earth Drillers, Except Oil and Gas",
+            "6821": "Excavating and loading machine and dragline operators, surface mining",
+            "6825": "Earth drillers, except oil and gas",
+            "6835": "Explosives workers, ordnance handling experts, and blasters",
+            "6840": "Mining Machine Operators",
+            "6850": "Underground mining machine operators",
+            "6910": "Roof Bolters, Mining",
+            "6920": "Roustabouts, oil and gas",
+            "6930": "Helpers--Extraction Workers",
+            "6940": "Other Extraction Workers",
+            "6950": "Other extraction workers",
+            "6999": "Installation, maintenance, and repair occupations",
+            "7000": "First-line supervisors of mechanics, installers, and repairers",
+            "7010": "Computer, automated teller, and office machine repairers",
+            "7020": "Radio and telecommunications equipment installers and repairers",
+            "7030": "Avionics technicians",
+            "7040": "Electric motor, power tool, and related repairers",
+            "7050": "Electrical and electronics installers and repairers, transportation equipment",
+            "7100": "Electrical and electronics repairers, industrial and utility",
+            "7110": "Electronic equipment installers and repairers, motor vehicles",
+            "7120": "Electronic home entertainment equipment installers and repairers",
+            "7130": "Security and fire alarm systems installers",
+            "7140": "Aircraft mechanics and service technicians",
+            "7150": "Automotive body and related repairers",
+            "7160": "Automotive glass installers and repairers",
+            "7200": "Automotive service technicians and mechanics",
+            "7210": "Bus and truck mechanics and diesel engine specialists",
+            "7220": "Heavy vehicle and mobile equipment service technicians and mechanics",
+            "7240": "Small engine mechanics",
+            "7260": "Miscellaneous vehicle and mobile equipment mechanics, installers, and repairers",
+            "7300": "Control and valve installers and repairers",
+            "7315": "Heating, air conditioning, and refrigeration mechanics and installers",
+            "7320": "Home appliance repairers",
+            "7330": "Industrial and refractory machinery mechanics",
+            "7340": "Industrial and refractory machinery mechanics",
+            "7350": "Maintenance workers, machinery",
+            "7360": "Millwrights",
+            "7410": "Electrical power-line installers and repairers",
+            "7420": "Telecommunications line installers and repairers",
+            "7430": "Precision instrument and equipment repairers",
+            "7440": "Wind turbine service technicians",
+            "7510": "Coin, vending, and amusement machine servicers and repairers",
+            "7520": "Commercial divers",
+            "7540": "Locksmiths and safe repairers",
+            "7550": "Manufactured building and mobile home installers",
+            "7560": "Riggers",
+            "7600": "Signal and Track Switch Repairers",
+            "7610": "Helpers, installation, maintenance, and repair workers",
+            "7630": "Other Installation, Maintenance, and Repair Workers",
+            "7640": "Other installation, maintenance, and repair workers",
+            "7698": "Production, transportation, and material moving occupations",
+            "7699": "Production occupations",
+            "7700": "First-line supervisors of production and operating workers",
+            "7710": "Aircraft structure, surfaces, rigging, and systems assemblers",
+            "7720": "Electrical, electronics, and electromechanical assemblers",
+            "7730": "Engine and other machine assemblers",
+            "7740": "Structural metal fabricators and fitters",
+            "7750": "Other assemblers and fabricators",
+            "7800": "Bakers",
+            "7810": "Butchers and other meat, poultry, and fish processing workers",
+            "7830": "Food and tobacco roasting, baking, and drying machine operators and tenders",
+            "7840": "Food batchmakers",
+            "7850": "Food cooking machine operators and tenders",
+            "7855": "Food processing workers, all other",
+            "7905": "Computer numerically controlled tool programmers and operators",
+            "7920": "Extruding and Drawing Machine Setters, Operators, and Tenders, Metal and Plastic",
+            "7925": "Forming machine setters, operators, and tenders, metal and plastic",
+            "7930": "Forging Machine Setters, Operators, and Tenders, Metal and Plastic",
+            "7940": "Rolling Machine Setters, Operators, and Tenders, Metal and Plastic",
+            "7950": "Cutting, punching, and press machine setters, operators, and tenders, metal and plastic",
+            "7960": "Drilling and Boring Machine Tool Setters, Operators, and Tenders, Metal and Plastic",
+            "8000": "Grinding, lapping, polishing, and buffing machine tool setters, operators, and tenders, metal and pl",
+            "8010": "Lathe and Turning Machine Tool Setters, Operators, and Tenders, Metal and Plastic",
+            "8020": "Milling and Planing Machine Setters, Operators, and Tenders, Metal and Plastic",
+            "8025": "Other machine tool setters, operators, and tenders, metal and plastic",
+            "8030": "Machinists",
+            "8040": "Metal furnace operators, tenders, pourers, and casters",
+            "8060": "Model makers and patternmakers, metal and plastic",
+            "8100": "Molders and molding machine setters, operators, and tenders, metal and plastic",
+            "8120": "Multiple Machine Tool Setters, Operators, and Tenders, Metal and Plastic",
+            "8130": "Tool and die makers",
+            "8140": "Welding, soldering, and brazing workers",
+            "8150": "Heat Treating Equipment Setters, Operators, and Tenders, Metal and Plastic",
+            "8160": "Layout Workers, Metal and Plastic",
+            "8200": "Plating and Coating Machine Setters, Operators, and Tenders, Metal and Plastic",
+            "8210": "Tool Grinders, Filers, and Sharpeners",
+            "8220": "Metal Workers and Plastic Workers, All Other",
+            "8225": "Other metal workers and plastic workers",
+            "8240": "Job Printers",
+            "8250": "Prepress technicians and workers",
+            "8255": "Printing press operators",
+            "8256": "Print binding and finishing workers",
+            "8260": "Printing Machine Operators",
+            "8300": "Laundry and dry-cleaning workers",
+            "8310": "Pressers, textile, garment, and related materials",
+            "8320": "Sewing machine operators",
+            "8330": "Shoe and Leather Workers and Repairers",
+            "8335": "Shoe and leather workers",
+            "8340": "Shoe Machine Operators and Tenders",
+            "8350": "Tailors, dressmakers, and sewers",
+            "8360": "Textile Bleaching and Dyeing Machine Operators and Tenders",
+            "8365": "Textile machine setters, operators, and tenders",
+            "8400": "Textile Cutting Machine Setters, Operators, and Tenders",
+            "8410": "Textile Knitting and Weaving Machine Setters, Operators, and Tenders",
+            "8420": "Textile Winding, Twisting, and Drawing Out Machine Setters, Operators, and Tenders",
+            "8430": "Extruding and Forming Machine Setters, Operators, and Tenders, Synthetic and Glass Fibers",
+            "8440": "Fabric and Apparel Patternmakers",
+            "8450": "Upholsterers",
+            "8460": "Textile, Apparel, and Furnishings Workers, All Other",
+            "8465": "Other textile, apparel, and furnishings workers",
+            "8500": "Cabinetmakers and bench carpenters",
+            "8510": "Furniture finishers",
+            "8520": "Model Makers and Patternmakers, Wood",
+            "8530": "Sawing machine setters, operators, and tenders, wood",
+            "8540": "Woodworking machine setters, operators, and tenders, except sawing",
+            "8550": "Woodworkers, All Other",
+            "8555": "Other woodworkers",
+            "8600": "Power plant operators, distributors, and dispatchers",
+            "8610": "Stationary engineers and boiler operators",
+            "8620": "Water and wastewater treatment plant and system operators",
+            "8630": "Miscellaneous plant and system operators",
+            "8640": "Chemical processing machine setters, operators, and tenders",
+            "8650": "Crushing, grinding, polishing, mixing, and blending workers",
+            "8710": "Cutting workers",
+            "8720": "Extruding, forming, pressing, and compacting machine setters, operators, and tenders",
+            "8730": "Furnace, kiln, oven, drier, and kettle operators and tenders",
+            "8740": "Inspectors, testers, sorters, samplers, and weighers",
+            "8750": "Jewelers and precious stone and metal workers",
+            "8760": "Dental and ophthalmic laboratory technicians and medical appliance technicians",
+            "8800": "Packaging and filling machine operators and tenders",
+            "8810": "Painting workers",
+            "8830": "Photographic process workers and processing machine operators",
+            "8840": "Semiconductor Processors",
+            "8850": "Adhesive bonding machine operators and tenders",
+            "8860": "Cleaning, Washing, and Metal Pickling Equipment Operators and Tenders",
+            "8865": "Other production equipment operators and tenders",
+            "8900": "Cooling and Freezing Equipment Operators and Tenders",
+            "8910": "Etchers and engravers",
+            "8920": "Molders, shapers, and casters, except metal and plastic",
+            "8930": "Paper goods machine setters, operators, and tenders",
+            "8940": "Tire builders",
+            "8950": "Helpers, production workers",
+            "8965": "Production Workers, All Other",
+            "8990": "Other production workers",
+            "8999": "Transportation and material moving occupations",
+            "9005": "Supervisors of transportation and material moving workers",
+            "9030": "Aircraft pilots and flight engineers",
+            "9040": "Air traffic controllers and airfield operations specialists",
+            "9050": "Flight attendants",
+            "9110": "Ambulance drivers and attendants, except emergency medical technicians",
+            "9120": "Bus Drivers",
+            "9121": "Bus drivers, school",
+            "9122": "Bus drivers, transit and intercity",
+            "9130": "Driver/sales workers and truck drivers",
+            "9140": "Taxi Drivers and Chauffeurs",
+            "9141": "Shuttle drivers and chauffeurs",
+            "9142": "Taxi drivers",
+            "9150": "Motor vehicle operators, all other",
+            "9200": "Locomotive Engineers and Operators",
+            "9210": "Locomotive engineers and operators",
+            "9230": "Railroad Brake, Signal, and Switch Operators",
+            "9240": "Railroad conductors and yardmasters",
+            "9260": "Subway, Streetcar, and Other Rail Transportation Workers",
+            "9265": "Other rail transportation workers",
+            "9300": "Sailors and marine oilers",
+            "9310": "Ship and boat captains and operators",
+            "9330": "Ship engineers",
+            "9340": "Bridge and Lock Tenders",
+            "9350": "Parking attendants",
+            "9360": "Automotive and Watercraft Service Attendants",
+            "9365": "Transportation service attendants",
+            "9410": "Transportation inspectors",
+            "9415": "Passenger attendants",
+            "9420": "Other Transportation Workers",
+            "9430": "Other transportation workers",
+            "9500": "Conveyor Operators and Tenders",
+            "9510": "Crane and tower operators",
+            "9520": "Dredge, Excavating, and Loading Machine Operators",
+            "9560": "Hoist and Winch Operators",
+            "9570": "Conveyor, dredge, and hoist and winch operators",
+            "9600": "Industrial truck and tractor operators",
+            "9610": "Cleaners of vehicles and equipment",
+            "9620": "Laborers and freight, stock, and material movers, hand",
+            "9630": "Machine feeders and offbearers",
+            "9640": "Packers and packagers, hand",
+            "9645": "Stockers and order fillers",
+            "9650": "Pumping station operators",
+            "9720": "Refuse and recyclable material collectors",
+            "9730": "Mine Shuttle Car Operators",
+            "9740": "Tank Car, Truck, and Ship Loaders",
+            "9750": "Material Moving Workers, All Other",
+            "9760": "Other material moving workers"
+        },
+        "education_code": {
+            "00": "All educational levels",
+            "10": "Some High School or High School Graduate",
+            "11": "Less than a High School diploma",
+            "12": "Less than 1 year of High School",
+            "15": "1 to 3 years of high school",
+            "16": "4 years of High School, no diploma",
+            "18": "High school graduates or more",
+            "19": "High School graduates, no college",
+            "20": "Some college or associate degree",
+            "21": "Some college, no degree",
+            "25": "Associate degree",
+            "26": "Associate degree, occupational program",
+            "27": "Associate degree, academic program",
+            "30": "Less than a high school diploma (discontinued)",
+            "31": "High school graduates, no college (discontinued)",
+            "32": "Some college, no degree (discontinued)",
+            "33": "College graduates (discontinued)",
+            "34": "Associate degree (discontinued)",
+            "35": "Less than a bachelor's degree (discontinued)",
+            "36": "Some college or associate degree (discontinued)",
+            "37": "Bachelor's degree only (discontinued)",
+            "38": "Advanced degree (discontinued)",
+            "39": "Bachelor's degree and higher (discontinued)",
+            "40": "Bachelor's degree and higher",
+            "41": "Bachelor's degree only",
+            "45": "Advanced degree",
+            "46": "Master's degree",
+            "47": "Professional degree",
+            "48": "Doctoral degree"
+        },
+        "ages_code": {
+            "00": "16 years and over",
+            "08": "16 to 19 years",
+            "10": "16 to 24 years",
+            "20": "20 to 24 years",
+            "28": "25 years and over",
+            "30": "25 to 29 years",
+            "31": "25 to 34 years",
+            "33": "25 to 54 years",
+            "36": "30 to 34 years",
+            "37": "35 to 39 years",
+            "38": "35 to 44 years",
+            "39": "40 to 44 years",
+            "41": "45 to 49 years",
+            "42": "45 to 54 years",
+            "44": "50 to 54 years",
+            "45": "55 years and over",
+            "48": "55 to 59 years",
+            "49": "55 to 64 years",
+            "57": "60 to 64 years",
+            "65": "65 years and over",
+            "66": "65 to 69 years",
+            "72": "70 years and over"
+        },
+        "race_code": {
+            "00": "All Races",
+            "01": "White",
+            "03": "Black or African American",
+            "04": "Asian"
+        },
+        "orig_code": {
+            "00": "All Origins",
+            "01": "Hispanic or Latino",
+            "10": "Non-Hispanic"
+        },
+        "sexs_code": {
+            "0": "Both Sexes",
+            "1": "Men",
+            "2": "Women"
+        },
+        "born_code": {
+            "00": null,
+            "01": "Native born",
+            "02": "Foreign born"
+        },
+        "footnote_code": {
+            "7": "Data do not meet publication criteria.",
+            "C": "Corrected"
+        }
+    },
+    "lu": {
+        "lfst_code": {
+            "20": "Employed",
+            "25": "Employed full time",
+            "26": "Employed part time"
+        },
+        "fips_code": {
+            "00": "U.S. Total",
+            "01": "Alabama",
+            "02": "Alaska",
+            "04": "Arizona",
+            "05": "Arkansas",
+            "06": "California",
+            "08": "Colorado",
+            "09": "Connecticut",
+            "10": "Delaware",
+            "11": "District of Columbia",
+            "12": "Florida",
+            "13": "Georgia",
+            "15": "Hawaii",
+            "16": "Idaho",
+            "17": "Illinois",
+            "18": "Indiana",
+            "19": "Iowa",
+            "20": "Kansas",
+            "21": "Kentucky",
+            "22": "Louisiana",
+            "23": "Maine",
+            "24": "Maryland",
+            "25": "Massachusetts",
+            "26": "Michigan",
+            "27": "Minnesota",
+            "28": "Mississippi",
+            "29": "Missouri",
+            "30": "Montana",
+            "31": "Nebraska",
+            "32": "Nevada",
+            "33": "New Hampshire",
+            "34": "New Jersey",
+            "35": "New Mexico",
+            "36": "New York",
+            "37": "North Carolina",
+            "38": "North Dakota",
+            "39": "Ohio",
+            "40": "Oklahoma",
+            "41": "Oregon",
+            "42": "Pennsylvania",
+            "44": "Rhode Island",
+            "45": "South Carolina",
+            "46": "South Dakota",
+            "47": "Tennessee",
+            "48": "Texas",
+            "49": "Utah",
+            "50": "Vermont",
+            "51": "Virginia",
+            "53": "Washington",
+            "54": "West Virginia",
+            "55": "Wisconsin",
+            "56": "Wyoming"
+        },
+        "tdata_code": {
+            "00": "Person counts (number in thousands)",
+            "01": "Percents/rates/ratios"
+        },
+        "pcts_code": {
+            "00": null,
+            "05": "Percent of employed within group"
+        },
+        "earn_code": {
+            "00": "Person counts (number in thousands)",
+            "01": "Median usual weekly earnings - in current dollars (second quartile)"
+        },
+        "class_code": {
+            "03": "Government wage and salary workers",
+            "04": "Federal wage and salary workers",
+            "05": "State wage and salary workers",
+            "06": "Local wage and salary workers",
+            "16": "Wage and salary workers, excluding incorporated self employed",
+            "17": "Private wage and salary workers, excluding incorporated self employed"
+        },
+        "unin_code": {
+            "0": null,
+            "1": "Members of unions",
+            "2": "Represented by unions",
+            "3": "Non-union"
+        },
+        "indy_code": {
+            "0000": "All Industries",
+            "0168": "Agriculture and related industries",
+            "0368": "Nonagriculture industries",
+            "0369": "Mining, quarrying, and oil and gas extraction",
+            "0569": "Utilities",
+            "0770": "Construction",
+            "1068": "Nondurable goods manufacturing",
+            "2467": "Manufacturing",
+            "2468": "Durable goods manufacturing",
+            "4067": "Wholesale and retail trade",
+            "4068": "Wholesale trade",
+            "4669": "Retail trade",
+            "6068": "Transportation and utilities",
+            "6069": "Transportation and warehousing",
+            "6468": "Information",
+            "6469": "Publishing, except Internet",
+            "6569": "Motion pictures and sound recording industries",
+            "6670": "Radio and television broadcasting and cable subscriptions programming",
+            "6679": "Telecommunications",
+            "6769": "Other information services",
+            "6867": "Financial activities",
+            "6868": "Finance and insurance",
+            "6869": "Finance",
+            "6990": "Insurance carriers and related activities",
+            "7069": "Real estate and rental and leasing",
+            "7268": "Professional and business services",
+            "7269": "Professional and technical services",
+            "7569": "Management, administrative, and waste services",
+            "7858": "Education and health services",
+            "7859": "Educational services",
+            "7968": "Health care and social assistance",
+            "8558": "Leisure and hospitality",
+            "8559": "Arts, entertainment, and recreation",
+            "8658": "Accommodation and food services",
+            "8659": "Accommodation",
+            "8679": "Food services and drinking places",
+            "8767": "Other services",
+            "8768": "Other services, except private households",
+            "9290": "Other services, private households"
+        },
+        "occupation_code": {
+            "0000": "All Occupations",
+            "0007": "Management, professional, and related occupations",
+            "0008": "Management, business, and financial operations occupations",
+            "0009": "Management occupations",
+            "0499": "Business and financial operations occupations",
+            "0998": "Professional and related occupations",
+            "0999": "Computer and mathematical occupations",
+            "1299": "Architecture and engineering occupations",
+            "1599": "Life, physical, and social science occupations",
+            "1999": "Community and social services occupations",
+            "2099": "Legal occupations",
+            "2199": "Education, training, and library occupations",
+            "2599": "Arts, design, entertainment, sports, and media occupations",
+            "2999": "Healthcare practitioner and technical occupations",
+            "3597": "Service occupations",
+            "3599": "Healthcare support occupations",
+            "3699": "Protective service occupations",
+            "3999": "Food preparation and serving related occupations",
+            "4199": "Building and grounds cleaning and maintenance occupations",
+            "4299": "Personal care and service occupations",
+            "4698": "Sales and office occupations",
+            "4699": "Sales and related occupations",
+            "4999": "Office and administrative support occupations",
+            "5998": "Natural resources, construction, and maintenance occupations",
+            "5999": "Farming, fishing, and forestry occupations",
+            "6199": "Construction and extraction occupations",
+            "6999": "Installation, maintenance, and repair occupations",
+            "7698": "Production, transportation, and material moving occupations",
+            "7699": "Production occupations",
+            "8999": "Transportation and material moving occupations"
+        },
+        "education_code": {
+            "00": null
+        },
+        "ages_code": {
+            "00": "16 years and over",
+            "10": "16 to 24 years",
+            "28": "25 years and over",
+            "31": "25 to 34 years",
+            "38": "35 to 44 years",
+            "42": "45 to 54 years",
+            "49": "55 to 64 years",
+            "65": "65 years and over"
+        },
+        "race_code": {
+            "00": "All Races",
+            "01": "White",
+            "03": "Black or African American",
+            "04": "Asian"
+        },
+        "orig_code": {
+            "00": "All Origins",
+            "01": "Hispanic or Latino"
+        },
+        "sexs_code": {
+            "0": "Both Sexes",
+            "1": "Men",
+            "2": "Women"
+        },
+        "footnote_code": {
+            "5": "1983-99 estimates exclude agricultural workers; as a result, 1983-99 private and government estimates will not sum to total.",
+            "7": "Data do not meet publication criteria."
+        }
+    }
+}

openbb_platform/providers/bls/openbb_bls/assets/cps_series.xz

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+size 150428

openbb_platform/providers/bls/openbb_bls/assets/ec_codes.json

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+{
+    "cm": {
+        "owner_code": {
+            "1": "Civilian workers",
+            "2": "Private industry workers",
+            "3": "State and local government workers"
+        },
+        "industry_code": {
+            "000000": "All workers",
+            "220000": "Utilities",
+            "230000": "Construction",
+            "300000": "Manufacturing",
+            "336411": "Aircraft manufacturing",
+            "400000": "Trade, transportation, and utilities",
+            "412000": "Retail trade",
+            "420000": "Wholesale trade",
+            "430000": "Transportation and warehousing",
+            "510000": "Information",
+            "520000": "Finance and insurance",
+            "520A00": "Financial activities",
+            "522000": "Credit intermediation",
+            "524000": "Insurance carriers",
+            "530000": "Real estate and rental and leasing",
+            "540000": "Professional, scientific, and technical services",
+            "540A00": "Professional and business services",
+            "560000": "Administrative and support and waste management and remediation services",
+            "600000": "Education and health services",
+            "610000": "Educational services",
+            "611100": "Elementary and secondary schools",
+            "612000": "Junior colleges, colleges, universities, and professional schools",
+            "620000": "Health care and social assistance",
+            "622000": "Hospitals",
+            "623000": "Nursing and residential care facilities",
+            "623100": "Nursing care facilities",
+            "700000": "Leisure and hospitality",
+            "720000": "Accommodation and food services",
+            "810000": "Other services (except public administration)",
+            "920000": "Public administration",
+            "DISCON": "Discontinued codes",
+            "G00000": "Goods producing",
+            "S00000": "Service providing"
+        },
+        "occupation_code": {
+            "000000": "All workers",
+            "111300": "Management, business, and financial occupations",
+            "112900": "Management, professional and related occupations",
+            "152900": "Professional and related occupations",
+            "250001": "Teachers",
+            "252000": "Primary, secondary, and special education school teachers",
+            "291111": "Registered nurses",
+            "313900": "Service occupations",
+            "410000": "Sales and related occupations",
+            "414300": "Sales and office occupations",
+            "430000": "Office and administrative support occupations",
+            "454700": "Construction, and extraction, farming, fishing, and forestry occupations",
+            "454900": "Natural resources, construction, and maintenance occupations",
+            "470000": "Construction and extraction occupations",
+            "490000": "Installation, maintenance, and repair occupations",
+            "510000": "Production occupations",
+            "515300": "Production, transportation, and material moving occupations",
+            "530000": "Transportation and material moving occupations",
+            "DISCON": "Discontinued Codes"
+        },
+        "subcell_code": {
+            "00": "All workers",
+            "01": "Less than 100 workers",
+            "02": "Less than 50 workers",
+            "04": "50-99 workers",
+            "05": "100 workers or more",
+            "06": "100-499 workers",
+            "07": "500 workers or more",
+            "23": "Union",
+            "24": "Nonunion",
+            "25": "Full time",
+            "26": "Part time",
+            "AA": "Establishment Size",
+            "AB": "Region and Division",
+            "AC": "Metropolitan Statistical Areas",
+            "AD": "Bargaining Status",
+            "AE": "Full-time and Part-time Work Status",
+            "AF": "Time and Incentive Status",
+            "AG": "Average Wage",
+            "AH": "Civilian Wage Percentiles",
+            "AI": "Private Wage Percentiles",
+            "AJ": "Government Wage Percentiles",
+            "AK": "Plan Sponsor"
+        },
+        "area_code": {
+            "00122": "Atlanta-Athens-Clarke County-Sandy Springs, GA CSA",
+            "00148": "Boston-Worcester-Providence, MA-RI-NH-CT CSA",
+            "00176": "Chicago-Naperville, IL-IN-WI CSA",
+            "00206": "Dallas-Fort Worth, TX-OK CSA",
+            "00220": "Detroit-Warren-Ann Arbor, MI CSA",
+            "00288": "Houston-The Woodlands, TX CSA",
+            "00348": "Los Angeles-Long Beach, CA CSA",
+            "00378": "Minneapolis-St. Paul, MN-WI CSA",
+            "00408": "New York-Newark, NY-NJ-CT-PA CSA",
+            "00428": "Philadelphia-Reading-Camden, PA-NJ-DE-MD CSA",
+            "00488": "San Jose-San Francisco-Oakland, CA CSA",
+            "00500": "Seattle-Tacoma, WA CSA",
+            "00548": "Washington-Baltimore-Arlington, DC-MD-VA-WV-PA CSA",
+            "33100": "Miami-Fort Lauderdale-Port St. Lucie, FL CSA",
+            "38060": "Phoenix-Mesa-Scottsdale, AZ MSA",
+            "98100": "Northeast census region",
+            "98200": "South census region",
+            "98300": "Midwest census region",
+            "98400": "West census region",
+            "98999": "Regions, divisions, and statistical areas",
+            "99100": "New England census division",
+            "99120": "Middle Atlantic census division",
+            "99130": "East South Central census division",
+            "99140": "South Atlantic census division",
+            "99150": "East North Central census division",
+            "99160": "West North Central census division",
+            "99170": "West South Central census division",
+            "99180": "Mountain census division",
+            "99190": "Pacific census division",
+            "99200": "Metropolitan statistical areas",
+            "99210": "Metropolitan",
+            "99220": "Nonmetropolitan",
+            "99999": "United States (National)"
+        },
+        "datatype_code": {
+            "D": "Cost of compensation (Cost per hour worked)",
+            "L": "Average employer cost per employee hour worked at 50th percentile (median), constant dollar",
+            "M": "Average employer cost per employee worked at 50th percentile (median), current dollar",
+            "N": "Average employer cost per employee hour worked at 90th percentile, current dollar",
+            "P": "Percent of total compensation",
+            "R": "Average employer cost per employee hour worked at 90th percentile, constant dollar",
+            "T": "Average employer cost per employee hour worked at 10th percentile, current dollar",
+            "X": "Average employer cost per employee hour worked at 10th percentile, constant dollar"
+        },
+        "estimate_code": {
+            "01": "Total compensation",
+            "02": "Wages and salaries",
+            "03": "Total benefits",
+            "04": "Paid leave",
+            "05": "Vacation",
+            "06": "Holiday",
+            "07": "Sick leave",
+            "08": "Personal leave",
+            "09": "Supplemental pay",
+            "10": "Overtime and premium pay",
+            "11": "Shift differentials",
+            "12": "Nonproduction bonuses",
+            "13": "Insurance",
+            "14": "Life insurance",
+            "15": "Health insurance",
+            "16": "Short-term disability insurance",
+            "17": "Long-term disability insurance",
+            "18": "Retirement and savings",
+            "19": "Defined benefit",
+            "20": "Defined contribution",
+            "21": "Legally Required benefits",
+            "22": "Social Security and Medicare",
+            "23": "Social Security",
+            "24": "Medicare",
+            "25": "Federal unemployment insurance",
+            "26": "State unemployment insurance",
+            "27": "Workers' compensation",
+            "28": "Other benefits"
+        },
+        "footnote_code": {
+            "2": "Registered Nurses estimates from December 2013 forward are based on the 2010 Standard Occupational Classification. For more information on classification changes, please see www.bls.gov/soc.",
+            "3": "Estimates from December 2013 to March 2014 for this series were corrected, details are available at www.bls.gov/bls/ecec_correction_091014.htm",
+            "4": "The relative standard error for this estimate is equal to or greater than 30 percent.",
+            "5": "The relative standard error is not available for percent of total compensation estimates.",
+            "6": "The relative standard error for this estimate is not currently available.",
+            "8": "The relative standard error is not available as the cost per hour worked is $0.01 or less.",
+            "A": "Cost per hour worked is $0.01 or less.",
+            "B": "Less than .05 percent.",
+            "C": "See <a href=\"http://www.bls.gov/ncs/ect/mapnote.htm#C\" target=\"new\">www.bls.gov/ncs/ect/mapnote.htm</a> for the definition of civilian workers.",
+            "D": "See <a href=\"http://www.bls.gov/ncs/ect/mapnote.htm#D\" target=\"new\">www.bls.gov/ncs/ect/mapnote.htm</a> for the definition of the goods-producing sector.",
+            "E": "See <a href=\"http://www.bls.gov/ncs/ect/mapnote.htm#E\" target=\"new\">www.bls.gov/ncs/ect/mapnote.htm</a> for the definition of the service-providing sector.",
+            "F": "Includes premium pay for work in addition to the regular work schedule (for example, overtime).",
+            "G": "Comprises the Old-Age, Survivors, and Disability Insurance (OASDI) program.",
+            "H": "Includes severance pay and supplemental unemployment benefits.",
+            "I": "The states that compose the New England census division are: CT, ME, MA, NH, RI, and VT.",
+            "J": "The states that compose the Middle Atlantic census division are: NJ, NY, and PA.",
+            "K": "The states that compose the South Atlantic census division are: DE, DC, FL, GA, MD, NC, SC, VA, and WV.",
+            "L": "The states that compose the East South Central census division are: AL, KY, MS, and TN.",
+            "M": "The states that compose the West South Central census division are: AR, LA, OK, and TX.",
+            "N": "The states that compose the East North Central census division are: IL, IN, MI, OH, and WI.",
+            "O": "The states that compose the West North Central census division are: IA, KS, MN, MO, NE, ND, and SD.",
+            "S": "The states that compose the Mountain census division are: AZ, CO, ID, MT, NV, NM, UT, and WY.",
+            "T": "The states that compose the Pacific census division are: AK, CA, HI, OR, and WA.",
+            "W": "Includes all teachers; see <a href=\"http://www.bls.gov/ncs/ect/mapnote.htm#W\" target=\"new\">www.bls.gov/ncs/ect/mapnote.htm</a> for details.",
+            "X": "See <a href=\"http://www.bls.gov/ncs/ect/mapnote.htm#X\" target=\"new\">www.bls.gov/ncs/ect/mapnote.htm</a> which is about the State and local government workforce.",
+            "Y": "See <a href=\"http://www.bls.gov/ncs/ect/mapnote.htm#Y\" target=\"new\">www.bls.gov/ncs/ect/mapnote.htm</a> for details regarding the Other benefits series.",
+            "Z": "Series discontinued beginning December 2008."
+        }
+    },
+    "cc": {
+        "sector_code": {
+            "1": "All Civilian",
+            "2": "Private industry",
+            "4": "Private goods producing",
+            "5": "Private service producing",
+            "6": "Private manufacturing",
+            "7": "Private nonmanufacturing",
+            "8": "Private health services",
+            "9": "Private hospitals",
+            "0": "Private nursing homes",
+            "3": "State and local government"
+        },
+        "benefit_code": {
+            "10000": "Total compensation",
+            "20000": "Wages and salaries",
+            "30000": "Total benefits",
+            "40000": "Paid leave",
+            "50000": "Supplemental pay",
+            "60000": "Insurance",
+            "70000": "Retirement and savings",
+            "80000": "Legally required benefits",
+            "90000": "Other benefits",
+            "A0000": "Vacation",
+            "B0000": "Holiday",
+            "C0000": "Sick",
+            "D0000": "Other",
+            "E0000": "Premium",
+            "F0000": "Shift differentials",
+            "G0000": "Nonproduction bonuses",
+            "H0000": "Life",
+            "I0000": "Health",
+            "J0000": "Short-term disability",
+            "K0000": "Long-term disability",
+            "L0000": "Pensions",
+            "M0000": "Savings and thrift",
+            "P0000": "Social Security",
+            "Q0000": "Old Age, Survivors, and Disability Income (OASDI)",
+            "R0000": "Medicare",
+            "S0000": "Federal unemployment insurance",
+            "T0000": "State unemployment insurance",
+            "U0000": "Workers' compensation",
+            "V0000": "Defined benefit",
+            "W0000": "Defined contribution"
+        },
+        "industryocc_code": {
+            "000001": "Occupational group",
+            "000002": "Industry",
+            "000003": "Region",
+            "000004": "Union/Nonunion",
+            "000006": "Metropolitan/Nonmetropolitan",
+            "000008": "Aerospace",
+            "000009": "Full-time/Part-time",
+            "000010": "Establishment size",
+            "002000": "1-99 workers",
+            "004000": "100 or more workers",
+            "006000": "100-499 workers",
+            "008000": "500 or more workers",
+            "012000": "1-99 workers, goods producing",
+            "014000": "100 or more workers, goods producing",
+            "016000": "100-499 workers, goods producing",
+            "018000": "500 or more workers, goods producing",
+            "022000": "1-99 workers, service producing",
+            "024000": "100 or more workers, service producing",
+            "026000": "100-499 workers, service producing",
+            "028000": "500 or more workers, service producing",
+            "032000": "1-99 workers, white collar",
+            "034000": "100 or more workers, white collar",
+            "036000": "100-499 workers, white collar",
+            "038000": "500 or more workers, white collar",
+            "042000": "1-99 workers, blue collar",
+            "044000": "100 or more workers, blue collar",
+            "046000": "100-499 workers, blue collar",
+            "048000": "500 or more workers, blue collar",
+            "100000": "All workers",
+            "101000": "Production and nonsupervisory occupations",
+            "106000": "Civilian workers, excluding sales",
+            "107000": "Civilian white collar workers, excluding sales",
+            "110000": "White collar workers",
+            "111000": "Executive, administrative, and managerial",
+            "112000": "Professional specialty and technical occupations",
+            "113000": "Sales workers",
+            "114000": "Administrative support, including clerical workers",
+            "115000": "Professional specialty occupations",
+            "116000": "Nurses",
+            "117000": "Teachers",
+            "118000": "Technical",
+            "120000": "Blue collar occupations",
+            "121000": "Precision production, craft, and repair occupation",
+            "122000": "Machine operators, assemblers, and inspectors",
+            "123000": "Transportation and material moving occupations",
+            "124000": "Handlers, equipment cleaners, helpers, and laborer",
+            "130000": "Service occupations",
+            "131000": "Private industry workers, excluding sales",
+            "132000": "Private industry white collar workers, excluding s",
+            "137000": "Wholesale and retail trade occupations, excluding",
+            "138000": "Finance, insurance, and real estate occupations, e",
+            "140000": "Wholesale trade occupations, excluding sales",
+            "151000": "White collar occupations, transportation equipment",
+            "152000": "Professional and technical occupations, transporta",
+            "153000": "Executive, administrative, and managerial occupati",
+            "154000": "Blue collar occupations, transportation equipment",
+            "155000": "Service occupations, transportation equipment",
+            "161000": "White collar occupations, aicraft manufacturing",
+            "164000": "Blue collar occupations, aircraft manufacturing",
+            "171000": "White collar occupations, transportation and publi",
+            "174000": "Blue collar occupations, transportation and public",
+            "181000": "White collar occupations, communications",
+            "184000": "Blue collar occupations, communications",
+            "191000": "White collar occupations, utilities",
+            "194000": "Blue collar occupations, utilities",
+            "200000": "Goods producing industries",
+            "201000": "Goods producing, excluding sales",
+            "202000": "Goods producing, white collar occupations",
+            "203000": "Goods producing, white collar occupations, excludi",
+            "204000": "Goods producing, blue collar occupations",
+            "206000": "Goods producing, service occupations",
+            "210000": "Service producing industries",
+            "211000": "Service producing, excluding sales",
+            "212000": "Service producing, white collar occupations",
+            "213000": "Service producing, white collar occupations, exclu",
+            "214000": "Service producing, blue collar occupations",
+            "216000": "Service producing, service occupations",
+            "220000": "Nonmanufacturing",
+            "221000": "Nonmanufacturing, white collar occupations",
+            "222000": "Nonmanufacturing, white collar occupations, exclud",
+            "223000": "Nonmanufacturing, blue collar occupations",
+            "225000": "Nonmanufacturing, service occupations",
+            "230000": "Construction",
+            "237000": "Manufacturing, transportation equipment",
+            "238000": "Manufacturing, aircraft",
+            "240000": "Manufacturing",
+            "241000": "Manufacturing, durable goods",
+            "242000": "Manufacturing, nondurables",
+            "243000": "Manufacturing, white collar occupations",
+            "250000": "Transportation and public utilities",
+            "251000": "Transportation",
+            "252000": "Public utilities",
+            "253000": "Communications",
+            "254000": "Electric, gas, and sanitation",
+            "260000": "Wholesale and retail trade",
+            "261000": "Wholesale trade",
+            "262000": "Retail trade",
+            "263000": "General merchandise stores",
+            "264000": "Food stores",
+            "270000": "Finance, insurance, and real estate",
+            "271000": "Banking",
+            "272000": "Insurance",
+            "273000": "Insurance, excluding sales",
+            "280000": "Services",
+            "281000": "Schools",
+            "282000": "Elementary and secondary schools",
+            "284000": "Health services",
+            "285000": "Hospitals",
+            "286000": "Nursing homes",
+            "289000": "Educational services",
+            "290000": "Public administration",
+            "299000": "Higher education",
+            "310000": "Northeast",
+            "320000": "South",
+            "330000": "Midwest",
+            "340000": "West",
+            "400000": "Union workers",
+            "402000": "Union, blue collar",
+            "406000": "Union, manufacturing, blue collar",
+            "410000": "Union, manufacturing",
+            "420000": "Union, nonmanufacturing",
+            "430000": "Union, goods producing",
+            "440000": "Union, service producing",
+            "500000": "Nonunion workers",
+            "502000": "Nonunion, blue collar",
+            "506000": "Nonunion, manufacturing, blue collar",
+            "510000": "Nonunion, manufacturing",
+            "520000": "Nonunion, nonmanufacturing",
+            "530000": "Nonunion, goods producing",
+            "540000": "Nonunion, service producing",
+            "600000": "Metropolitan areas",
+            "700000": "Nonmetropolitan areas",
+            "800000": "Aircraft engine parts",
+            "801000": "White collar",
+            "802000": "Professional, technical, and specialty",
+            "805000": "Managers",
+            "806000": "Clerical",
+            "807000": "Blue collar",
+            "808000": "Craft",
+            "809000": "Operatives",
+            "810000": "Aircraft",
+            "811000": "White collar",
+            "812000": "Blue collar",
+            "820000": "Engines",
+            "821000": "White collar",
+            "822000": "Blue collar",
+            "830000": "Parts",
+            "831000": "White collar",
+            "832000": "Blue collar",
+            "840000": "Guided missiles",
+            "841000": "White collar",
+            "842000": "Blue collar",
+            "910000": "All full-time workers",
+            "911000": "Full-time, white collar",
+            "912000": "Full-time, sales",
+            "913000": "Full-time, administrative",
+            "914000": "Full-time, blue collar",
+            "915000": "Full-time, service",
+            "921000": "Full-time, goods producing",
+            "922000": "Full-time, construction",
+            "923000": "Full-time, manufacturing",
+            "924000": "Full-time, service producing",
+            "925000": "Full-time, transportation",
+            "926000": "Full-time, wholesale trade",
+            "927000": "Full-time, retail trade",
+            "928000": "Full-time, finance, insurance, and real estate",
+            "929000": "Full-time, services",
+            "950000": "All part-time workers",
+            "951000": "Part-time, white collar",
+            "952000": "Part-time, sales",
+            "953000": "Part-time, administrative",
+            "954000": "Part-time, blue collar",
+            "955000": "Part-time, service",
+            "961000": "Part-time, goods producing",
+            "963000": "Part-time, manufacturing",
+            "964000": "Part-time, service producing",
+            "965000": "Part-time, transportation",
+            "966000": "Part-time, wholesale trade",
+            "967000": "Part-time, retail trade",
+            "968000": "Part-time, finance, insurance, and real estate",
+            "969000": "Part-time, services"
+        },
+        "costfactor_code": {
+            "D": "Cost of compensation (Cost per hour worked)",
+            "P": "Percent of total compensation"
+        },
+        "footnote_code": {
+            "A": "Cost per hour worked is $0.01 or less.",
+            "B": "Less than .05 percent."
+        }
+    }
+}

openbb_platform/providers/bls/openbb_bls/assets/ec_series.xz

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+version https://git-lfs.github.com/spec/v1
+oid sha256:eff71c3a0d5ec14c878c589ffbdb904eb245af187629000c9fd6016aae86b164
+size 105140

openbb_platform/providers/bls/openbb_bls/assets/ip_codes.json

@@ -0,0 +1,1136 @@
+{
+    "ip": {
+        "sector_code": {
+            "A": "Agriculture, Forestry, Fishing and Hunting",
+            "B": "Mining",
+            "C": "Utilities",
+            "D": "Construction",
+            "E": "Manufacturing",
+            "G": "Wholesale Trade",
+            "H": "Retail Trade",
+            "I": "Transportation and Warehousing",
+            "J": "Information",
+            "K": "Finance and Insurance",
+            "L": "Real Estate and Rental and Leasing",
+            "M": "Professional, Scientific, and Technical Services",
+            "O": "Management of Companies and Enterprises",
+            "P": "Administrative and Support and Waste Management and Remediation Services",
+            "Q": "Educational Services",
+            "R": "Health Care and Social Assistance",
+            "S": "Arts, Entertainment, and Recreation",
+            "T": "Accommodation and Food Services",
+            "U": "Other Services (except Public Administration)",
+            "W": "Government",
+            "Z": "Multi-Sector"
+        },
+        "industry_code": {
+            "D11____": "Agriculture, forestry, fishing, and hunting",
+            "D21____": "Mining",
+            "D22____": "Utilities",
+            "D23____": "Construction",
+            "D31_33_": "Manufacturing",
+            "D42____": "Wholesale trade",
+            "D44_45_": "Retail trade",
+            "D48_49_": "Transportation and warehouseing",
+            "D512___": "Motion picture and sound recording industries",
+            "D517___": "Telecommunications",
+            "D51____": "Information",
+            "D52____": "Finance and insurance",
+            "D53____": "Real estate and rental and leasing",
+            "D54192_": "Photographic Services",
+            "D54____": "Professional, scientific, and technical services",
+            "D55____": "Management of companies and enterprises",
+            "D5613__": "Employment services",
+            "D5617__": "Services to buildings and dwellings",
+            "D56____": "Administrative and support and waste management and remediation services",
+            "D61____": "Educational services",
+            "D62____": "Health care and social assistance",
+            "D71____": "Arts, entertainment, and recreation",
+            "D72____": "Accommodation and food services",
+            "D8122__": "Death care services",
+            "D8129__": "Other personal services",
+            "D81____": "Other services (except public administration)",
+            "D90____": "Government",
+            "D______": "Private Nonfarm",
+            "N1111__": "Oilseed and grain farming",
+            "N11121_": "Vegetable and melon farming",
+            "N1112__": "Vegetable and melon farming",
+            "N1113__": "Fruit and tree nut farming",
+            "N1114__": "Greenhouse, nursery, and floriculture production",
+            "N1119__": "Other crop farming",
+            "N111___": "Crop production",
+            "N1121__": "Cattle ranching and farming",
+            "N112210": "Hog and pig farming",
+            "N11221_": "Hog and pig farming",
+            "N1122__": "Hog and pig farming",
+            "N1123__": "Poultry and egg production",
+            "N1124__": "Sheep and goat farming",
+            "N11251_": "Aquaculture",
+            "N1125__": "Aquaculture",
+            "N1129__": "Other animal production",
+            "N112___": "Animal production",
+            "N113110": "Timber tract operations",
+            "N11311_": "Timber tract operations",
+            "N1131__": "Timber tract operations",
+            "N113210": "Forest nurseries and gathering of forest products",
+            "N11321_": "Forest nurseries and gathering of forest products",
+            "N1132__": "Forest nurseries and gathering of forest products",
+            "N113310": "Logging",
+            "N11331_": "Logging",
+            "N1133__": "Logging",
+            "N113___": "Forestry and logging",
+            "N11411_": "Fishing",
+            "N1141__": "Fishing",
+            "N114210": "Hunting and trapping",
+            "N11421_": "Hunting and trapping",
+            "N1142__": "Hunting and trapping",
+            "N114___": "Fishing, hunting and trapping",
+            "N11511_": "Support activities for crop production",
+            "N1151__": "Support activities for crop production",
+            "N115210": "Support activities for animal production",
+            "N11521_": "Support activities for animal production",
+            "N1152__": "Support activities for animal production",
+            "N115310": "Support activities for forestry",
+            "N11531_": "Support activities for forestry",
+            "N1153__": "Support activities for forestry",
+            "N115___": "Support activities for agriculture and forestry",
+            "N2111__": "Oil and gas extraction",
+            "N211___": "Oil and gas extraction",
+            "N21211_": "Coal mining",
+            "N2121__": "Coal mining",
+            "N2122__": "Metal ore mining",
+            "N21231_": "Stone Mining and Quarrying",
+            "N21232_": "Sand, Gravel, Clay, and Ceramic and Refractory Minerals Mining and Quarrying",
+            "N21239_": "Other Nonmetallic Mineral Mining and Quarrying",
+            "N2123__": "Nonmetallic mineral mining and quarrying",
+            "N212___": "Mining (except oil and gas)",
+            "N21311_": "Support activities for mining",
+            "N2131__": "Support activities for mining",
+            "N213___": "Support activities for mining",
+            "N21____": "Mining",
+            "N2211__": "Electric power generation, transmission and distribution",
+            "N221210": "Natural gas distribution",
+            "N22121_": "Natural gas distribution",
+            "N2212__": "Natural gas distribution",
+            "N2213__": "Water, sewage and other systems",
+            "N221___": "Utilities",
+            "N22____": "Utilities",
+            "N23611_": "Residential building construction",
+            "N2361__": "Residential building construction",
+            "N2362__": "Nonresidential building construction",
+            "N236___": "Construction of buildings",
+            "N2371__": "Utility system construction",
+            "N237210": "Land subdivision",
+            "N23721_": "Land subdivision",
+            "N2372__": "Land subdivision",
+            "N237310": "Highway, street, and bridge construction",
+            "N23731_": "Highway, street, and bridge construction",
+            "N2373__": "Highway, street, and bridge construction",
+            "N237990": "Other heavy and civil engineering construction",
+            "N23799_": "Other heavy and civil engineering construction",
+            "N2379__": "Other heavy and civil engineering construction",
+            "N237___": "Heavy and civil engineering construction",
+            "N2381__": "Building foundation and exterior contractors",
+            "N2382__": "Building equipment contractors",
+            "N2383__": "Building finishing contractors",
+            "N2389__": "Other specialty trade contractors",
+            "N238___": "Specialty trade contractors",
+            "N31111_": "Animal food manufacturing",
+            "N3111__": "Animal food manufacturing",
+            "N3112__": "Grain and oilseed milling",
+            "N3113__": "Sugar and confectionery product manufacturing",
+            "N31141_": "Frozen food manufacturing",
+            "N31142_": "Fruit and vegetable canning, pickling, and drying",
+            "N3114__": "Fruit and vegetable preserving and specialty food manufacturing",
+            "N3115__": "Dairy product manufacturing",
+            "N311615": "Poultry processing",
+            "N31161_": "Animal slaughtering and processing",
+            "N3116__": "Animal slaughtering and processing",
+            "N311710": "Seafood product preparation and packaging",
+            "N31171_": "Seafood product preparation and packaging",
+            "N3117__": "Seafood product preparation and packaging",
+            "N3118__": "Bakeries and tortilla manufacturing",
+            "N3119__": "Other food manufacturing",
+            "N311___": "Food manufacturing",
+            "N3121__": "Beverage manufacturing",
+            "N312230": "Tobacco manufacturing",
+            "N31223_": "Tobacco manufacturing",
+            "N3122__": "Tobacco manufacturing",
+            "N312___": "Beverage and tobacco product manufacturing",
+            "N313110": "Fiber, yarn, and thread mills",
+            "N31311_": "Fiber, yarn, and thread mills",
+            "N3131__": "Fiber, yarn, and thread mills",
+            "N3132__": "Fabric mills",
+            "N3133__": "Textile and fabric finishing and fabric coating mills",
+            "N313___": "Textile mills",
+            "N3141__": "Textile furnishings mills",
+            "N3149__": "Other textile product mills",
+            "N314___": "Textile product mills",
+            "N3151__": "Apparel knitting mills",
+            "N3152__": "Cut and sew apparel manufacturing",
+            "N315990": "Apparel accessories and other apparel manufacturing",
+            "N31599_": "Apparel accessories and other apparel manufacturing",
+            "N3159__": "Apparel accessories and other apparel manufacturing",
+            "N315___": "Apparel manufacturing",
+            "N316110": "Leather and hide tanning and finishing",
+            "N31611_": "Leather and hide tanning and finishing",
+            "N3161__": "Leather and hide tanning and finishing",
+            "N316210": "Footwear manufacturing",
+            "N31621_": "Footwear manufacturing",
+            "N3162__": "Footwear manufacturing",
+            "N31699_": "Other leather and allied product manufacturing",
+            "N3169__": "Other leather and allied product manufacturing",
+            "N316___": "Leather and allied product manufacturing",
+            "N32111_": "Sawmills and wood preservation",
+            "N3211__": "Sawmills and wood preservation",
+            "N32121_": "Veneer, plywood, and engineered wood product manufacturing",
+            "N3212__": "Veneer, plywood, and engineered wood product manufacturing",
+            "N32191_": "Millwork",
+            "N321920": "Wood container and pallet manufacturing",
+            "N32192_": "Wood container and pallet manufacturing",
+            "N32199_": "All other wood product manufacturing",
+            "N3219__": "Other wood product manufacturing",
+            "N321___": "Wood product manufacturing",
+            "N3221__": "Pulp, paper, and paperboard mills",
+            "N32221_": "Paperboard container manufacturing",
+            "N3222__": "Converted paper product manufacturing",
+            "N322___": "Paper manufacturing",
+            "N3231__": "Printing and related support activities",
+            "N323___": "Printing and related support activities",
+            "N3241__": "Petroleum and coal products manufacturing",
+            "N324___": "Petroleum and coal products manufacturing",
+            "N3251__": "Basic chemical manufacturing",
+            "N3252__": "Resin, synthetic rubber, and artificial synthetic fibers and filaments manufacturing",
+            "N3253__": "Pesticide, fertilizer, and other agricultural chemical manufacturing",
+            "N32541_": "Pharmaceutical and medicine manufacturing",
+            "N3254__": "Pharmaceutical and medicine manufacturing",
+            "N3255__": "Paint, coating, and adhesive manufacturing",
+            "N3256__": "Soap, cleaning compound, and toilet preparation manufacturing",
+            "N3259__": "Other chemical product and preparation manufacturing",
+            "N325___": "Chemical manufacturing",
+            "N32619_": "Other plastics product manufacturing",
+            "N3261__": "Plastics product manufacturing",
+            "N3262__": "Rubber product manufacturing",
+            "N326___": "Plastics and rubber products manufacturing",
+            "N3271__": "Clay product and refractory manufacturing",
+            "N32721_": "Glass and glass product manufacturing",
+            "N3272__": "Glass and glass product manufacturing",
+            "N327320": "Ready-mix concrete manufacturing",
+            "N32732_": "Ready-mix concrete manufacturing",
+            "N3273__": "Cement and concrete product manufacturing",
+            "N3274__": "Lime and gypsum product manufacturing",
+            "N3279__": "Other nonmetallic mineral product manufacturing",
+            "N327___": "Nonmetallic mineral product manufacturing",
+            "N331110": "Iron and steel mills and ferroalloy production",
+            "N33111_": "Iron and steel mills and ferroalloy production",
+            "N3311__": "Iron and steel mills and ferroalloy production",
+            "N3312__": "Steel product manufacturing from purchased steel",
+            "N33131_": "Alumina and aluminum production and processing",
+            "N3313__": "Alumina and aluminum production and processing",
+            "N3314__": "Nonferrous metal (except aluminum) production and processing",
+            "N3315__": "Foundries",
+            "N331___": "Primary metal manufacturing",
+            "N33211_": "Forging and stamping",
+            "N3321__": "Forging and stamping",
+            "N33221_": "Cutlery and handtool manufacturing",
+            "N3322__": "Cutlery and handtool manufacturing",
+            "N332312": "Fabricated structural metals",
+            "N33231_": "Plate work and fabricated structural product manufacturing",
+            "N332322": "Sheet metal work",
+            "N33232_": "Ornamental and architectural metal products manufacturing",
+            "N3323__": "Architectural and structural metals manufacturing",
+            "N3324__": "Boiler, tank, and shipping container manufacturing",
+            "N332510": "Hardware manufacturing",
+            "N33251_": "Hardware manufacturing",
+            "N3325__": "Hardware manufacturing",
+            "N33261_": "Spring and wire product manufacturing",
+            "N3326__": "Spring and wire product manufacturing",
+            "N332710": "Machine shops",
+            "N33271_": "Machine shops",
+            "N33272_": "Turned product and screw, nut, and bolt manufacturing",
+            "N3327__": "Machine shops; turned product; and screw, nut, and bolt manufacturing",
+            "N332813": "Electroplating, plating, polishing, anodizing and coloring",
+            "N33281_": "Coating, engraving, heat treating, and allied activities",
+            "N3328__": "Coating, engraving, heat treating, and allied activities",
+            "N33291_": "Metal valve manufacturing",
+            "N33299_": "All other fabricated metal product manufacturing",
+            "N3329__": "Other fabricated metal product manufacturing",
+            "N332___": "Fabricated metal product manufacturing",
+            "N3331__": "Agriculture, construction, and mining machinery",
+            "N33324_": "Industrial machinery",
+            "N3332__": "Industrial machinery",
+            "N33331_": "Commercial and service industry machinery",
+            "N3333__": "Commercial and service industry machinery",
+            "N33341_": "Ventilation, heating, air-conditioning, and commercial refrigeration equipment manufacturing",
+            "N3334__": "Ventilation, heating, air-conditioning, and commercial refrigeration equipment manufacturing",
+            "N333514": "Special die and tool, die set, jig, and fixture manufacturing",
+            "N333517": "Machine tool manufacturing",
+            "N33351_": "Metalworking machinery manufacturing",
+            "N3335__": "Metalworking machinery manufacturing",
+            "N33361_": "Engine, turbine, and power transmission equipment manufacturing",
+            "N3336__": "Engine, turbine, and power transmission equipment manufacturing",
+            "N33392_": "Material handling equipment manufacturing",
+            "N3339__": "Other general purpose machinery manufacturing",
+            "N333___": "Machinery manufacturing",
+            "N33411_": "Computer and peripheral equipment manufacturing",
+            "N3341__": "Computer and peripheral equipment manufacturing",
+            "N3342__": "Communications equipment manufacturing",
+            "N334310": "Audio and video equipment manufacturing",
+            "N33431_": "Audio and video equipment manufacturing",
+            "N3343__": "Audio and video equipment manufacturing",
+            "N334413": "Semiconductor and related device manufacturing",
+            "N33441_": "Semiconductor and other electronic component manufacturing",
+            "N3344__": "Semiconductor and other electronic component manufacturing",
+            "N33451_": "Navigational, measuring, electromedical, and control instruments manufacturing",
+            "N3345__": "Navigational, measuring, electromedical, and control instruments manufacturing",
+            "N33461_": "Manufacturing and reproducing magnetic and optical media",
+            "N3346__": "Manufacturing and reproducing magnetic and optical media",
+            "N334___": "Computer and electronic product manufacturing",
+            "N3351__": "Electric lighting equipment manufacturing",
+            "N3352__": "Household appliance manufacturing",
+            "N33531_": "Electrical equipment manufacturing",
+            "N3353__": "Electrical equipment manufacturing",
+            "N3359__": "Other electrical equipment and component manufacturing",
+            "N335___": "Electrical equipment, appliance, and component manufacturing",
+            "N3361__": "Motor vehicle manufacturing",
+            "N33621_": "Motor vehicle body and trailer manufacturing",
+            "N3362__": "Motor vehicle body and trailer manufacturing",
+            "N336320": "Motor vehicle electrical and electronic equipment",
+            "N33632_": "Motor vehicle electrical and electronic equipment",
+            "N3363__": "Motor vehicle parts manufacturing",
+            "N336411": "Aircraft manufacturing",
+            "N33641_": "Aerospace product and parts manufacturing",
+            "N3364__": "Aerospace product and parts manufacturing",
+            "N336510": "Railroad rolling stock manufacturing",
+            "N33651_": "Railroad rolling stock manufacturing",
+            "N3365__": "Railroad rolling stock manufacturing",
+            "N33661_": "Ship and boat building",
+            "N3366__": "Ship and boat building",
+            "N33699_": "Other transportation equipment manufacturing",
+            "N3369__": "Other transportation equipment manufacturing",
+            "N336___": "Transportation equipment manufacturing",
+            "N337110": "Wood kitchen cabinet and countertop manufacturing",
+            "N33711_": "Wood kitchen cabinet and countertop manufacturing",
+            "N33712_": "Household and institutional furniture manufacturing",
+            "N3371__": "Household and institutional furniture and kitchen cabinet manufacturing",
+            "N33721_": "Office furniture (including fixtures) manufacturing",
+            "N3372__": "Office furniture (including fixtures) manufacturing",
+            "N3379__": "Other furniture related product manufacturing",
+            "N337___": "Furniture and related product manufacturing",
+            "N339113": "Surgical appliance and supplies manufacturing",
+            "N33911_": "Medical equipment and supplies manufacturing",
+            "N3391__": "Medical equipment and supplies manufacturing",
+            "N339950": "Sign manufacturing",
+            "N33995_": "Sign manufacturing",
+            "N3399__": "Other miscellaneous manufacturing",
+            "N339___": "Miscellaneous manufacturing",
+            "N4231__": "Motor vehicle and motor vehicle parts and supplies merchant wholesalers",
+            "N4232__": "Furniture and home furnishing merchant wholesalers",
+            "N4233__": "Lumber and other construction materials merchant wholesalers",
+            "N4234__": "Professional and commercial equipment and supplies merchant wholesalers",
+            "N4235__": "Metal and mineral (except petroleum) merchant wholesalers",
+            "N4236__": "Electrical and electronic goods merchant wholesalers",
+            "N4237__": "Hardware, and plumbing and heating equipment and supplies merchant wholesalers",
+            "N4238__": "Machinery, equipment, and supplies merchant wholesalers",
+            "N4239__": "Miscellaneous durable goods merchant wholesalers",
+            "N423___": "Merchant wholesalers, durable goods",
+            "N4241__": "Paper and paper product merchant wholesalers",
+            "N424210": "Drugs and druggists' sundries merchant wholesalers",
+            "N42421_": "Drugs and druggists' sundries merchant wholesalers",
+            "N4242__": "Drugs and druggists' sundries merchant wholesalers",
+            "N4243__": "Apparel, piece goods, and notions merchant wholesalers",
+            "N4244__": "Grocery and related product wholesalers",
+            "N4245__": "Farm product raw material merchant wholesalers",
+            "N4246__": "Chemical and allied products merchant wholesalers",
+            "N4247__": "Petroleum and petroleum products merchant wholesalers",
+            "N4248__": "Beer, wine, and distilled alcoholic beverage merchant wholesalers",
+            "N4249__": "Miscellaneous nondurable goods merchant wholesalers",
+            "N424___": "Merchant wholesalers, nondurable goods",
+            "N4251__": "Wholesale electronic markets and agents and brokers",
+            "N425___": "Wholesale electronic markets and agents and brokers",
+            "N42____": "Wholesale trade",
+            "N441110": "New car dealers",
+            "N44111_": "New car dealers",
+            "N441120": "Used car dealers",
+            "N44112_": "Used car dealers",
+            "N4411__": "Automobile dealers",
+            "N4412__": "Other motor vehicle dealers",
+            "N441310": "Automotive parts and accessories stores",
+            "N44131_": "Automotive parts and accessories stores",
+            "N441320": "Tire dealers",
+            "N44132_": "Tire dealers",
+            "N4413__": "Automotive parts, accessories, and tire stores",
+            "N441___": "Motor vehicle and parts dealers",
+            "N442110": "Furniture stores",
+            "N44211_": "Furniture stores",
+            "N4421__": "Furniture stores",
+            "N442210": "Floor covering stores",
+            "N44221_": "Floor covering stores",
+            "N44229_": "Other home furnishings stores",
+            "N4422__": "Home furnishings stores",
+            "N442___": "Furniture and home furnishings stores",
+            "N443141": "Household appliance stores",
+            "N443142": "Electronics stores",
+            "N44314_": "Electronics and appliance stores",
+            "N4431__": "Electronics and appliance stores",
+            "N443___": "Electronics and appliance stores",
+            "N444110": "Home centers",
+            "N44411_": "Home centers",
+            "N444130": "Hardware stores",
+            "N44413_": "Hardware stores",
+            "N4441__": "Building material and supplies dealers",
+            "N444210": "Outdoor power equipment stores",
+            "N44421_": "Outdoor power equipment stores",
+            "N444220": "Nursery, garden center, and farm supply stores",
+            "N44422_": "Nursery, garden center, and farm supply stores",
+            "N4442__": "Lawn and garden equipment and supplies stores",
+            "N444___": "Building material and garden equipment and supplies dealers",
+            "N445110": "Supermarkets and other grocery (except convenience) stores",
+            "N44511_": "Supermarkets and other grocery (except convenience) stores",
+            "N445120": "Convenience stores",
+            "N44512_": "Convenience stores",
+            "N4451__": "Grocery stores",
+            "N4452__": "Specialty food stores",
+            "N445310": "Beer, wine, and liquor stores",
+            "N44531_": "Beer, wine, and liquor stores",
+            "N4453__": "Beer, wine, and liquor stores",
+            "N445___": "Food and beverage stores",
+            "N446110": "Pharmacies and drug stores",
+            "N44611_": "Pharmacies and drug stores",
+            "N446120": "Cosmetics, beauty supplies, and perfume stores",
+            "N44612_": "Cosmetics, beauty supplies, and perfume stores",
+            "N446130": "Optical goods stores",
+            "N44613_": "Optical goods stores",
+            "N44619_": "Other health and personal care stores",
+            "N4461__": "Health and personal care stores",
+            "N446___": "Health and personal care stores",
+            "N447110": "Gasoline stations with convenience stores",
+            "N44711_": "Gasoline stations with convenience stores",
+            "N447190": "Other gasoline stations",
+            "N44719_": "Other gasoline stations",
+            "N4471__": "Gasoline stations",
+            "N447___": "Gasoline stations",
+            "N4481__": "Clothing stores",
+            "N448210": "Shoe stores",
+            "N44821_": "Shoe stores",
+            "N4482__": "Shoe stores",
+            "N4483__": "Jewelry, luggage, and leather goods stores",
+            "N448___": "Clothing and clothing accessories stores",
+            "N44_45_": "Retail trade",
+            "N451110": "Sporting goods stores",
+            "N45111_": "Sporting goods stores",
+            "N451120": "Hobby, toy, and game stores",
+            "N45112_": "Hobby, toy, and game stores",
+            "N4511__": "Sporting goods, hobby, and musical instrument stores",
+            "N45121_": "Book stores and news dealers",
+            "N4512__": "Book stores and news dealers",
+            "N451___": "Sporting goods, hobby, book, and music stores",
+            "N452210": "Department stores",
+            "N45221_": "Department stores",
+            "N4522__": "Department stores",
+            "N45231_": "General merchandise stores, including warehouse clubs and supercenters",
+            "N4523__": "General merchandise stores, including warehouse clubs and supercenters",
+            "N452___": "General merchandise stores",
+            "N453110": "Florists",
+            "N45311_": "Florists",
+            "N4531__": "Florists",
+            "N453210": "Office supplies and stationery stores",
+            "N45321_": "Office supplies and stationery stores",
+            "N453220": "Gift, novelty, and souvenir stores",
+            "N45322_": "Gift, novelty, and souvenir stores",
+            "N4532__": "Office supplies, stationery, and gift stores",
+            "N453310": "Used merchandise stores",
+            "N45331_": "Used merchandise stores",
+            "N4533__": "Used merchandise stores",
+            "N453910": "Pet and pet supplies stores",
+            "N45391_": "Pet and pet supplies stores",
+            "N4539__": "Other miscellaneous store retailers",
+            "N453___": "Miscellaneous store retailers",
+            "N45411_": "Electronic shopping and mail-order houses",
+            "N4541__": "Electronic shopping and mail-order houses",
+            "N454210": "Vending machine operators",
+            "N45421_": "Vending machine operators",
+            "N4542__": "Vending machine operators",
+            "N454310": "Fuel dealers",
+            "N45431_": "Fuel dealers",
+            "N454390": "Other direct selling establishments",
+            "N45439_": "Other direct selling establishments",
+            "N4543__": "Direct selling establishments",
+            "N454___": "Nonstore retailers",
+            "N48111_": "Scheduled air transportation",
+            "N4811__": "Scheduled air transportation",
+            "N48121_": "Nonscheduled air transportation",
+            "N4812__": "Nonscheduled air transportation",
+            "N481___": "Air transportation",
+            "N482111": "Line-haul railroads",
+            "N48211_": "Rail transportation",
+            "N4821__": "Rail transportation",
+            "N482___": "Rail transportation",
+            "N48311_": "Deep sea, coastal, and Great Lakes water transportation",
+            "N4831__": "Deep sea, coastal, and Great Lakes water transportation",
+            "N48321_": "Inland water transportation",
+            "N4832__": "Inland water transportation",
+            "N483___": "Water transportation",
+            "N484110": "General freight trucking, local",
+            "N48411_": "General freight trucking, local",
+            "N48412_": "General freight trucking, long-distance",
+            "N4841__": "General freight trucking",
+            "N484210": "Used household and office goods moving",
+            "N48421_": "Used household and office goods moving",
+            "N484220": "Specialized freight (except used goods) trucking, local",
+            "N48422_": "Specialized freight (except used goods) trucking, local",
+            "N484230": "Specialized freight (except used goods) trucking, long-distance",
+            "N48423_": "Specialized freight (except used goods) trucking, long-distance",
+            "N4842__": "Specialized freight trucking",
+            "N484___": "Truck transportation",
+            "N48511_": "Urban transit systems",
+            "N4851__": "Urban transit systems",
+            "N485210": "Interurban and rural bus transportation",
+            "N48521_": "Interurban and rural bus transportation",
+            "N4852__": "Interurban and rural bus transportation",
+            "N4853__": "Taxi and limousine service",
+            "N485410": "School and employee bus transportation",
+            "N48541_": "School and employee bus transportation",
+            "N4854__": "School and employee bus transportation",
+            "N485510": "Charter bus industry",
+            "N48551_": "Charter bus industry",
+            "N4855__": "Charter bus industry",
+            "N48599_": "Other transit and ground passenger transportation",
+            "N4859__": "Other transit and ground passenger transportation",
+            "N485___": "Transit and ground passenger transportation",
+            "N486110": "Pipeline transportation of crude oil",
+            "N48611_": "Pipeline transportation of crude oil",
+            "N4861__": "Pipeline transportation of crude oil",
+            "N486210": "Pipeline transportation of natural gas",
+            "N48621_": "Pipeline transportation of natural gas",
+            "N4862__": "Pipeline transportation of natural gas",
+            "N4869__": "Other pipeline transportation",
+            "N486___": "Pipeline transportation",
+            "N487110": "Scenic and sightseeing transportation, land",
+            "N48711_": "Scenic and sightseeing transportation, land",
+            "N4871__": "Scenic and sightseeing transportation, land",
+            "N487210": "Scenic and sightseeing transportation, water",
+            "N48721_": "Scenic and sightseeing transportation, water",
+            "N4872__": "Scenic and sightseeing transportation, water",
+            "N487990": "Scenic and sightseeing transportation, other",
+            "N48799_": "Scenic and sightseeing transportation, other",
+            "N4879__": "Scenic and sightseeing transportation, other",
+            "N487___": "Scenic and sightseeing transportation",
+            "N4881__": "Support activities for air transportation",
+            "N488210": "Support activities for rail transportation",
+            "N48821_": "Support activities for rail transportation",
+            "N4882__": "Support activities for rail transportation",
+            "N4883__": "Support activities for water transportation",
+            "N4884__": "Support activities for road transportation",
+            "N488510": "Freight transportation arrangement",
+            "N48851_": "Freight transportation arrangement",
+            "N4885__": "Freight transportation arrangement",
+            "N48899_": "Other support activities for transportation",
+            "N4889__": "Other support activities for transportation",
+            "N488___": "Support activities for transportation",
+            "N491110": "Postal service",
+            "N49111_": "Postal service",
+            "N4911__": "Postal service",
+            "N491___": "Postal service",
+            "N492110": "Couriers and express delivery services",
+            "N49211_": "Couriers and express delivery services",
+            "N4921__": "Couriers and express delivery services",
+            "N492210": "Local messengers and local delivery",
+            "N49221_": "Local messengers and local delivery",
+            "N4922__": "Local messengers and local delivery",
+            "N492___": "Couriers and messengers",
+            "N493110": "General warehousing and storage",
+            "N49311_": "General warehousing and storage",
+            "N493120": "Refrigerated warehousing and storage",
+            "N49312_": "Refrigerated warehousing and storage",
+            "N4931__": "Warehousing and storage",
+            "N493___": "Warehousing and storage",
+            "N511110": "Newspaper publishers",
+            "N51111_": "Newspaper publishers",
+            "N511120": "Periodical publishers",
+            "N51112_": "Periodical publishers",
+            "N511130": "Book publishers",
+            "N51113_": "Book publishers",
+            "N5111__": "Newspaper, periodical, book, and directory publishers",
+            "N511210": "Software publishers",
+            "N51121_": "Software publishers",
+            "N5112__": "Software publishers",
+            "N511___": "Publishing industries (except internet)",
+            "N51213_": "Motion picture and video exhibition",
+            "N5121__": "Motion picture and video industries",
+            "N5122__": "Sound recording industries",
+            "N512___": "Motion picture and sound recording industries",
+            "N51511_": "Radio broadcasting",
+            "N5151__": "Radio and television broadcasting",
+            "N515210": "Cable and other subscription programming",
+            "N51521_": "Cable and other subscription programming",
+            "N5152__": "Cable and other subscription programming",
+            "N515___": "Broadcasting (except internet)",
+            "N517311": "Wired Telecommunications Carriers",
+            "N517312": "Wireless Telecommunications Carriers (except Satellite)",
+            "N51731_": "Wired and Wireless Telecommunications Carriers",
+            "N5173__": "Wired and Wireless Telecommunications Carriers",
+            "N517410": "Satellite telecommunications",
+            "N51741_": "Satellite telecommunications",
+            "N5174__": "Satellite telecommunications",
+            "N51791_": "Other telecommunications",
+            "N5179__": "Other telecommunications",
+            "N517___": "Telecommunications",
+            "N518210": "Data processing, hosting, and related services",
+            "N51821_": "Data processing, hosting, and related services",
+            "N5182__": "Data processing, hosting, and related services",
+            "N518___": "Data processing, hosting, and related services",
+            "N5191__": "Other information services",
+            "N519___": "Other information services",
+            "N521110": "Monetary authorities-central bank",
+            "N52111_": "Monetary authorities-central bank",
+            "N5211__": "Monetary authorities-central bank",
+            "N521___": "Monetary authorities-central bank",
+            "N522110": "Commercial banking",
+            "N52211_": "Commercial banking",
+            "N5221__": "Depository credit intermediation",
+            "N5222__": "Nondepository credit intermediation",
+            "N5223__": "Activities related to credit intermediation",
+            "N522___": "Credit intermediation and related activities",
+            "N5231__": "Securities and commodity contracts intermediation and brokerage",
+            "N523210": "Securities and commodity exchanges",
+            "N52321_": "Securities and commodity exchanges",
+            "N5232__": "Securities and commodity exchanges",
+            "N5239__": "Other financial investment activities",
+            "N523___": "Securities, commodity contracts, investments",
+            "N5241__": "Insurance carriers",
+            "N5242__": "Insurance agencies, brokerages, and related services",
+            "N524___": "Insurance carriers and related activities",
+            "N5251__": "Insurance and employee benefit funds",
+            "N5259__": "Other investment pools and funds",
+            "N525___": "Funds, trusts, and other financial vehicles",
+            "N5311__": "Lessors of real estate",
+            "N531210": "Offices of real estate agents and brokers",
+            "N53121_": "Offices of real estate agents and brokers",
+            "N5312__": "Offices of real estate agents and brokers",
+            "N5313__": "Activities related to real estate",
+            "N531___": "Real estate",
+            "N532111": "Passenger car rental",
+            "N532120": "Truck, utility trailer, and rv (recreational vehicle) rental and leasing",
+            "N53212_": "Truck, utility trailer, and rv (recreational vehicle) rental and leasing",
+            "N5321__": "Automotive equipment rental and leasing",
+            "N532282": "Video Tape and Disc Rental",
+            "N5322__": "Consumer goods rental",
+            "N532310": "General rental centers",
+            "N53231_": "General rental centers",
+            "N5323__": "General rental centers",
+            "N5324__": "Machinery and equipment rental and leasing",
+            "N532___": "Rental and leasing services",
+            "N533110": "Lessors of nonfinancial intangible assets (except copyrighted works)",
+            "N53311_": "Lessors of nonfinancial intangible assets (except copyrighted works)",
+            "N5331__": "Lessors of nonfinancial intangible assets (except copyrighted works)",
+            "N533___": "Lessors of nonfinancial intangible assets (except copyrighted works)",
+            "N5411__": "Legal services",
+            "N541211": "Offices of certified public accountants",
+            "N541213": "Tax preparation services",
+            "N541219": "Other accounting services",
+            "N54121_": "Accounting, tax preparation, bookkeeping, and payroll services",
+            "N5412__": "Accounting, tax preparation, bookkeeping, and payroll services",
+            "N541310": "Architectural services",
+            "N54131_": "Architectural services",
+            "N541330": "Engineering services",
+            "N54133_": "Engineering services",
+            "N5413__": "Architectural and engineering services",
+            "N5414__": "Specialized design services",
+            "N54151_": "Computer systems design and related services",
+            "N5415__": "Computer systems design and related services",
+            "N5416__": "Management and technical consulting services",
+            "N5417__": "Scientific research and development services",
+            "N541810": "Advertising agencies",
+            "N54181_": "Advertising agencies",
+            "N5418__": "Advertising and related services",
+            "N541921": "Photography studios, portrait",
+            "N541940": "Veterinary services",
+            "N54194_": "Veterinary services",
+            "N5419__": "Other professional and technical services",
+            "N541___": "Professional, scientific, and technical services",
+            "N54____": "Professional, scientific, and technical services",
+            "N55111_": "Management of companies and enterprises",
+            "N5511__": "Management of companies and enterprises",
+            "N551___": "Management of companies and enterprises",
+            "N55____": "Management of companies and enterprises",
+            "N561110": "Office administrative services",
+            "N56111_": "Office administrative services",
+            "N5611__": "Office administrative services",
+            "N561210": "Facilities support services",
+            "N56121_": "Facilities support services",
+            "N5612__": "Facilities support services",
+            "N56131_": "Employment placement agencies and executive search services",
+            "N5613__": "Employment services",
+            "N5614__": "Business support services",
+            "N561510": "Travel agencies",
+            "N56151_": "Travel agencies",
+            "N5615__": "Travel arrangement and reservation services",
+            "N5616__": "Investigation and security services",
+            "N561720": "Janitorial services",
+            "N56172_": "Janitorial services",
+            "N5617__": "Services to buildings and dwellings",
+            "N5619__": "Other support services",
+            "N561___": "Administrative and support services",
+            "N56211_": "Waste collection",
+            "N5621__": "Waste collection",
+            "N56221_": "Waste treatment and disposal",
+            "N5622__": "Waste treatment and disposal",
+            "N5629__": "Remediation and other waste services",
+            "N562___": "Waste management and remediation services",
+            "N611110": "Elementary and secondary schools",
+            "N61111_": "Elementary and secondary schools",
+            "N6111__": "Elementary and secondary schools",
+            "N611210": "Junior colleges",
+            "N61121_": "Junior colleges",
+            "N6112__": "Junior colleges",
+            "N611310": "Colleges, universities, and professional schools",
+            "N61131_": "Colleges, universities, and professional schools",
+            "N6113__": "Colleges, universities, and professional schools",
+            "N6114__": "Business, computer, and management training",
+            "N61151_": "Technical and trade schools",
+            "N6115__": "Technical and trade schools",
+            "N6116__": "Other schools and instruction",
+            "N611710": "Educational support services",
+            "N61171_": "Educational support services",
+            "N6117__": "Educational support services",
+            "N611___": "Educational services",
+            "N61____": "Educational services",
+            "N62111_": "Offices of physicians",
+            "N6211__": "Offices of physicians",
+            "N621210": "Offices of dentists",
+            "N62121_": "Offices of dentists",
+            "N6212__": "Offices of dentists",
+            "N6213__": "Offices of other health practitioners",
+            "N6214__": "Outpatient care centers",
+            "N621511": "Medical laboratories",
+            "N621512": "Diagnostic imaging centers",
+            "N62151_": "Medical and diagnostic laboratories",
+            "N6215__": "Medical and diagnostic laboratories",
+            "N621610": "Home health care services",
+            "N62161_": "Home health care services",
+            "N6216__": "Home health care services",
+            "N6219__": "Other ambulatory health care services",
+            "N621___": "Ambulatory health care services",
+            "N622110": "General medical and surgical hospitals",
+            "N62211_": "General medical and surgical hospitals",
+            "N6221__": "General medical and surgical hospitals",
+            "N622210": "Psychiatric and substance abuse hospitals",
+            "N62221_": "Psychiatric and substance abuse hospitals",
+            "N6222__": "Psychiatric and substance abuse hospitals",
+            "N622310": "Specialty (except psychiatric and substance abuse) hospitals",
+            "N62231_": "Specialty (except psychiatric and substance abuse) hospitals",
+            "N6223__": "Specialty (except psychiatric and substance abuse) hospitals",
+            "N622A__": "Hospitals, except psychiatric and substance abuse hospitals",
+            "N622___": "Hospitals",
+            "N623110": "Nursing care facilities",
+            "N62311_": "Nursing care facilities",
+            "N6231__": "Nursing care facilities",
+            "N6232__": "Residential mental health facilities",
+            "N62331_": "Community care facilities for the elderly",
+            "N6233__": "Community care facilities for the elderly",
+            "N623990": "Other residential care facilities",
+            "N62399_": "Other residential care facilities",
+            "N6239__": "Other residential care facilities",
+            "N623___": "Nursing and residential care facilities",
+            "N6241__": "Individual and family services",
+            "N6242__": "Emergency and other relief services",
+            "N624310": "Vocational rehabilitation services",
+            "N62431_": "Vocational rehabilitation services",
+            "N6243__": "Vocational rehabilitation services",
+            "N624410": "Child day care services",
+            "N62441_": "Child day care services",
+            "N6244__": "Child day care services",
+            "N624___": "Social assistance",
+            "N7111__": "Performing arts companies",
+            "N71121_": "Spectator sports",
+            "N7112__": "Spectator sports",
+            "N7113__": "Arts and sports promoters and agents and managers for public figures",
+            "N711410": "Agents and managers for artists, athletes, entertainers, and other public figures",
+            "N71141_": "Agents and managers for artists, athletes, entertainers, and other public figures",
+            "N7114__": "Agents and managers for artists, athletes, entertainers, and other public figures",
+            "N711510": "Independent artists, writers, and performers",
+            "N71151_": "Independent artists, writers, and performers",
+            "N7115__": "Independent artists, writers, and performers",
+            "N711___": "Performing arts and spectator sports",
+            "N7121__": "Museums, historical sites, and similar institutions",
+            "N712___": "Museums, historical sites, and similar institutions",
+            "N713110": "Amusement and theme parks",
+            "N71311_": "Amusement and theme parks",
+            "N7131__": "Amusement parks and arcades",
+            "N7132__": "Gambling industries",
+            "N713910": "Golf courses and country clubs",
+            "N71391_": "Golf courses and country clubs",
+            "N713940": "Fitness and recreational sports centers",
+            "N71394_": "Fitness and recreational sports centers",
+            "N713950": "Bowling centers",
+            "N71395_": "Bowling centers",
+            "N7139__": "Other amusement and recreation industries",
+            "N713___": "Amusements, gambling, and recreation",
+            "N721110": "Hotels (except casino hotels) and motels",
+            "N72111_": "Hotels (except casino hotels) and motels",
+            "N7211__": "Traveler accommodation",
+            "N72121_": "RV (recreational vehicle) parks and recreational camps",
+            "N7212__": "RV (recreational vehicle) parks and recreational camps",
+            "N721310": "Rooming and boarding houses",
+            "N72131_": "Rooming and boarding houses",
+            "N7213__": "Rooming and boarding houses",
+            "N721___": "Accommodation",
+            "N7223__": "Special food services",
+            "N722410": "Drinking places (alcoholic beverages)",
+            "N72241_": "Drinking places (alcoholic beverages)",
+            "N7224__": "Drinking places (alcoholic beverages)",
+            "N722511": "Full-service restaurants",
+            "N72251A": "Limited-service eating places",
+            "N72251_": "Restaurants and other eating places",
+            "N7225__": "Restaurants and other eating places",
+            "N722___": "Food services and drinking places",
+            "N72____": "Accommodation and food services",
+            "N8111__": "Automotive repair and maintenance",
+            "N81121_": "Electronic and precision equipment repair and maintenance",
+            "N8112__": "Electronic and precision equipment repair and maintenance",
+            "N811310": "Commercial machinery repair and maintenance",
+            "N81131_": "Commercial machinery repair and maintenance",
+            "N8113__": "Commercial machinery repair and maintenance",
+            "N811420": "Reupholstery and furniture repair",
+            "N81142_": "Reupholstery and furniture repair",
+            "N8114__": "Household goods repair and maintenance",
+            "N811___": "Repair and maintenance",
+            "N81211_": "Hair, nail, and skin care services",
+            "N8121__": "Personal care services",
+            "N812210": "Funeral homes and funeral services",
+            "N81221_": "Funeral homes and funeral services",
+            "N8122__": "Death care services",
+            "N812310": "Coin-operated laundries and drycleaners",
+            "N81231_": "Coin-operated laundries and drycleaners",
+            "N812320": "Drycleaning and laundry services (except coin-operated)",
+            "N81232_": "Drycleaning and laundry services (except coin-operated)",
+            "N81233_": "Linen and uniform supply",
+            "N8123__": "Drycleaning and laundry services",
+            "N812910": "Pet care (except veterinary) services",
+            "N81291_": "Pet care (except veterinary) services",
+            "N81292_": "Photofinishing",
+            "N8129__": "Other personal services",
+            "N812___": "Personal and laundry services",
+            "N813110": "Religious organizations",
+            "N81311_": "Religious organizations",
+            "N8131__": "Religious organizations",
+            "N81321_": "Grantmaking and giving services",
+            "N8132__": "Grantmaking and giving services",
+            "N81331_": "Social advocacy organizations",
+            "N8133__": "Social advocacy organizations",
+            "N813410": "Civic and social organizations",
+            "N81341_": "Civic and social organizations",
+            "N8134__": "Civic and social organizations",
+            "N8139__": "Professional and similar organizations",
+            "N813___": "Membership associations and organizations",
+            "N814110": "Private households",
+            "N81411_": "Private households",
+            "N8141__": "Private households",
+            "N814___": "Private households",
+            "N901___": "Government (excluding postal service)",
+            "N______": "Private Nonfarm"
+        },
+        "measure_code": {
+            "C00": "Capital productivity (Index, 2017=100)",
+            "C01": "Capital input (Index, 2017=100)",
+            "C02": "Capital costs (Millions of current dollars)",
+            "C03": "Capital share (Percentage)",
+            "C06": "Capital intensity (Index, 2017=100)",
+            "C07": "Contribution of capital intensity to labor productivity (Index, 2017=100)",
+            "L00": "Labor productivity (Index, 2017=100)",
+            "L01": "Hours worked (Index, 2017=100)",
+            "L02": "Labor compensation (Millions of current dollars)",
+            "L03": "Labor share (Percentage)",
+            "L06": "Real labor compensation (Million $)",
+            "L07": "Real labor compensation (Index, 2017=100)",
+            "L20": "Hours worked (Millions of hours)",
+            "M00": "Total factor productivity (Index, 2017=100)",
+            "M01": "Combined inputs (Index, 2017=100)",
+            "M02": "Combined inputs costs (Millions of current dollars)",
+            "M05": "Combined inputs price deflator (Index, 2017=100)",
+            "P00": "Intermediate inputs productivity (Index, 2017=100)",
+            "P01": "Intermediate inputs (Index, 2017=100)",
+            "P02": "Intermediate inputs costs (Millions of current dollars)",
+            "P03": "Intermediate inputs share (Percentage)",
+            "P06": "Intermediate inputs intensity (Index, 2017=100)",
+            "P07": "Contribution of intermediate inputs intensity to labor productivity (Index, 2017=100)",
+            "T01": "Real sectoral output (Index, 2017=100)",
+            "T02": "Real value-added output (Index, 2017=100)",
+            "T05": "Sectoral output price deflator (Index, 2017=100)",
+            "T06": "Value-added output price deflator (Index, 2017=100)",
+            "T30": "Sectoral output (Millions of current dollars)",
+            "T39": "Value-added output (Millions of current dollars)",
+            "U10": "Unit labor costs (Index, 2017=100)",
+            "U11": "Labor compensation (Index, 2017=100)",
+            "U12": "Hourly compensation (Index, 2017=100)",
+            "U13": "Hourly compensation ($ / Hour)",
+            "U14": "Real hourly compensation ($ / Hour)",
+            "U15": "Real hourly labor compensation (Index, 2017=100)",
+            "W00": "Output per worker (Index, 2017=100)",
+            "W01": "Employment (Index, 2017=100)",
+            "W20": "Employment (Thousands of jobs)"
+        },
+        "duration_code": {
+            "0": "Indexes or values",
+            "1": "Annual percent changes"
+        },
+        "type_code": {
+            "E": "Employees",
+            "H": "Hours",
+            "I": "Index",
+            "P": "Percent",
+            "R": "Rate",
+            "Y": "Currency"
+        },
+        "area_code": {
+            "000000": "U.S. Total",
+            "010000": "Alabama",
+            "020000": "Alaska",
+            "040000": "Arizona",
+            "050000": "Arkansas",
+            "060000": "California",
+            "080000": "Colorado",
+            "090000": "Connecticut",
+            "100000": "Delaware",
+            "110000": "District of Columbia",
+            "120000": "Florida",
+            "130000": "Georgia",
+            "150000": "Hawaii",
+            "160000": "Idaho",
+            "170000": "Illinois",
+            "180000": "Indiana",
+            "190000": "Iowa",
+            "200000": "Kansas",
+            "210000": "Kentucky",
+            "220000": "Louisiana",
+            "230000": "Maine",
+            "240000": "Maryland",
+            "250000": "Massachusetts",
+            "260000": "Michigan",
+            "270000": "Minnesota",
+            "280000": "Mississippi",
+            "290000": "Missouri",
+            "300000": "Montana",
+            "310000": "Nebraska",
+            "320000": "Nevada",
+            "330000": "New Hampshire",
+            "340000": "New Jersey",
+            "350000": "New Mexico",
+            "360000": "New York",
+            "370000": "North Carolina",
+            "380000": "North Dakota",
+            "390000": "Ohio",
+            "400000": "Oklahoma",
+            "410000": "Oregon",
+            "420000": "Pennsylvania",
+            "440000": "Rhode Island",
+            "450000": "South Carolina",
+            "460000": "South Dakota",
+            "470000": "Tennessee",
+            "480000": "Texas",
+            "490000": "Utah",
+            "500000": "Vermont",
+            "510000": "Virginia",
+            "530000": "Washington",
+            "540000": "West Virginia",
+            "550000": "Wisconsin",
+            "560000": "Wyoming",
+            "981000": "Northeast Region",
+            "982000": "South Region",
+            "983000": "Midwest Region",
+            "984000": "West Region"
+        }
+    },
+    "pr": {
+        "sector_code": {
+            "3000": "Manufacturing",
+            "3100": "Manufacturing, Durable Goods",
+            "3200": "Manufacturing, Nondurable Goods",
+            "8400": "Business",
+            "8500": "Nonfarm Business",
+            "8800": "Nonfinancial Corporations"
+        },
+        "class_code": {
+            "3": "Employees",
+            "6": "All workers"
+        },
+        "measure_code": {
+            "01": "Employment",
+            "02": "Average weekly hours",
+            "03": "Hours worked",
+            "04": "Real value-added output",
+            "05": "Value-added output",
+            "06": "Labor compensation",
+            "08": "Nonlabor payments",
+            "09": "Labor productivity (output per hour)",
+            "10": "Hourly compensation",
+            "11": "Unit labor costs",
+            "12": "Unit nonlabor costs",
+            "13": "Unit nonlabor payments",
+            "14": "Value-added output price deflator",
+            "15": "Real hourly compensation",
+            "16": "Output per worker",
+            "17": "Labor share",
+            "18": "Profits",
+            "19": "Unit profits",
+            "20": "Unit combined input costs",
+            "21": "Real sectoral output",
+            "22": "Sectoral output price deflator",
+            "23": "Sectoral output"
+        },
+        "duration_code": {
+            "1": "% Change same quarter 1 year ago",
+            "2": "% Change from previous quarter",
+            "3": "Index (2017=100)"
+        },
+        "footnote_code": {
+            "R": "revised"
+        }
+    },
+    "mp": {
+        "sector_code": {
+            "0011": "Agriculture, forestry, fishing, and hunting (NAICS 11)",
+            "0021": "Mining (NAICS 21)",
+            "0022": "Utilities (NAICS 22)",
+            "0023": "Construction (NAICS 23)",
+            "0042": "Wholesale trade (NAICS 42)",
+            "0044": "Retail trade (NAICS 44,45)",
+            "0048": "Transportation and warehousing (NAICS 48-49)",
+            "0051": "Information (NAICS 51)",
+            "0052": "Finance and insurance (NAICS 52)",
+            "0053": "Real estate and rental and leasing (NAICS 53)",
+            "0054": "Professional, scientific, and technical services (NAICS 54)",
+            "0055": "Management of companies and enterprises (NAICS 55)",
+            "0056": "Administrative and waste management services (NAICS 56)",
+            "0061": "Educational services (NAICS 61)",
+            "0062": "Health care and social assistance (NAICS 62)",
+            "0071": "Arts, entertainment, and recreation (NAICS 71)",
+            "0072": "Accommodation and food services (NAICS 72)",
+            "0081": "Other services, except government (NAICS 81)",
+            "0111": "Crop & animal production (Farms) (NAICS 111,112)",
+            "0113": "Forestry, fishing, and related activities (NAICS 113-115)",
+            "0211": "Oil and gas extraction (NAICS 211)",
+            "0212": "Mining, except oil and gas (NAICS 212)",
+            "0213": "Support activities for mining (NAICS 213)",
+            "0481": "Air transportation (NAICS 481)",
+            "0482": "Rail transportation (NAICS 482)",
+            "0483": "Water transportation (NAICS 483)",
+            "0484": "Truck transportation (NAICS 484)",
+            "0485": "Transit and ground passenger transportation (NAICS 485)",
+            "0486": "Pipeline transportation (NAICS 486)",
+            "0487": "Other transportation and support activities (NAICS 487,488,492)",
+            "0493": "Warehousing and storage (NAICS 493)",
+            "0511": "Publishing industries, except internet (includes software) (NAICS 511)",
+            "0512": "Motion picture and sound recording industries (NAICS 512)",
+            "0515": "Broadcasting and telecommunications (NAICS 515,517)",
+            "0518": "Data processing, internet publishing, and other information services (NAICS 518,519)",
+            "0521": "Federal reserve banks, credit intermediation, and related activities (NAICS 521,522)",
+            "0523": "Securities, commodity contracts, and other financial investments and related activities (NAICS 523)",
+            "0524": "Insurance carriers and related activities (NAICS 524)",
+            "0525": "Funds, trusts, and other financial vehicles (NAICS 525)",
+            "0531": "Real estate (NAICS 531)",
+            "0532": "Rental and leasing services and lessors of nonfinancial and intangible assets (NAICS 532,533)",
+            "0561": "Administrative and support services (NAICS 561)",
+            "0562": "Waste management and remediation services (NAICS 562)",
+            "0621": "Ambulatory health care services (NAICS 621)",
+            "0622": "Hospitals and nursing and residential care facilities (NAICS 622,623)",
+            "0624": "Social assistance (NAICS 624)",
+            "0711": "Performing arts, spectator sports, museums, and related activities (NAICS 711,712)",
+            "0713": "Amusements, gambling, and recreation industries (NAICS 713)",
+            "0721": "Accommodation (NAICS 721)",
+            "0722": "Food services and drinking places (NAICS 722)",
+            "4244": "Trade (NAICS 42,44-45)",
+            "4900": "Private Business Sector (NAICS PG)",
+            "4910": "Private Nonfarm Business Sector (NAICS XG)",
+            "5000": "Wood products (NAICS 321)",
+            "5050": "Nonmetallic mineral products (NAICS 327)",
+            "5100": "Primary metal products (NAICS 331)",
+            "5150": "Fabricated metal products (NAICS 332)",
+            "5200": "Machinery (NAICS 333)",
+            "5250": "Computer and electronic products (NAICS 334)",
+            "5253": "Finance, insurance, real estate, and leasing (NAICS 52-53)",
+            "5300": "Electrical equipment, appliances, and components (NAICS 335)",
+            "5360": "Motor vehicles, bodies and trailers, and parts (NAICS 3361-3363)",
+            "5370": "Other transportation equipment (NAICS 3364-3369)",
+            "5400": "Furniture and related products (NAICS 337)",
+            "5411": "Legal services (NAICS 5411)",
+            "5412": "Miscellaneous professional, scientific, and technical services (NAICS 5412-5414,5416-5419)",
+            "5415": "Computer systems design and related services (NAICS 5415)",
+            "5450": "Miscellaneous manufacturing (NAICS 339)",
+            "5456": "Professional and business services (NAICS 54-56)",
+            "5481": "Services (NAICS 54-81)",
+            "5500": "Food and beverage and tobacco products (NAICS 311,312)",
+            "5550": "Textile mills and textile product mills (NAICS 313,314)",
+            "5600": "Apparel and leather and applied products (NAICS 315,316)",
+            "5650": "Paper products (NAICS 322)",
+            "5700": "Printing and related support activities (NAICS 323)",
+            "5750": "Petroleum and coal products (NAICS 324)",
+            "5800": "Chemical products (NAICS 325)",
+            "5850": "Plastics and rubber products (NAICS 326)",
+            "6162": "Educational services, health care, and social assistance (NAICS 61-62)",
+            "7172": "Arts, entertainment, recreation, accommodation, and food services (NAICS 71-72)",
+            "9900": "Manufacturing Sector (NAICS MN)",
+            "9910": "Nondurable Manufacturing Sector (NAICS ND)",
+            "9920": "Durable Manufacturing Sector (NAICS DM)"
+        },
+        "measure_code": {
+            "01": "Total factor productivity",
+            "02": "Real value-added output",
+            "03": "Combined inputs",
+            "04": "Capital input",
+            "05": "Labor input",
+            "06": "Labor productivity",
+            "07": "Capital productivity",
+            "08": "Capital intensity",
+            "09": "Labor composition",
+            "10": "Value-added output, billions of current dollars",
+            "11": "Capital costs, billions of current dollars",
+            "12": "Labor compensation, billions of current dollars",
+            "13": "Capital share",
+            "14": "Labor share",
+            "15": "Contribution of capital intensity to labor productivity",
+            "16": "Contribution of information processing equipment (IPE) intensity to labor productivity",
+            "17": "Contribution of capital input excluding IPP and IPE intensity to labor productivity",
+            "18": "Contribution of labor composition to labor productivity",
+            "19": "Contribution of research and development (R&D) intensity to labor productivity",
+            "20": "Contribution of intellectual property products (IPP) excluding R&D intensity to labor productivity",
+            "21": "Unit labor costs",
+            "22": "Unit capital costs",
+            "51": "Real sectoral output",
+            "55": "Energy input",
+            "56": "Materials input",
+            "57": "Services Input",
+            "61": "Sectoral output, billions of current dollars",
+            "62": "Capital costs, billions of current dollars",
+            "63": "Labor costs, billions of current dollars",
+            "64": "Energy costs, billions of current dollars",
+            "65": "Materials costs, billions of current dollars",
+            "66": "Services costs, billions of current dollars",
+            "67": "Capital share",
+            "68": "Labor share",
+            "69": "Energy share",
+            "70": "Materials share",
+            "71": "Services share",
+            "74": "Contribution of energy intensity to labor productivity",
+            "76": "Contribution of materials intensity to labor productivity",
+            "77": "Contribution of services intensity to labor productivity",
+            "78": "Contribution of intermediate inputs intensity to labor productivity"
+        },
+        "duration_code": {
+            "1": "Levels",
+            "2": "Indexes = 100.000",
+            "3": "% Change Year Ago"
+        },
+        "footnote_code": {
+            "00": "Tornqvist (rental price wts.) aggregate K inputs",
+            "01": "Tornqvist (cost share wts.) aggregate K and L",
+            "02": "Real Value-Added Output divided by combined inputs",
+            "03": "Tornqvist aggregate of hours by age, education, & gender",
+            "04": "Sectoral output per unit of combined K, L, E, M, S",
+            "06": "Combined K,  L, E, M, S, cost share weights",
+            "08": "Output per hour worked",
+            "09": "Ratio of Labor Input to Hours"
+        }
+    }
+}